{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 豆瓣电影Top 250 + 其他电影数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 项目介绍:豆瓣电影top250 + 电影数据的数据分析\n",
    "* 项目介绍：\n",
    "* 项目人:2019级网络与新媒体专业刘咏琳\n",
    "* 时间:2021年7月\n",
    "* 数据源：datas文件夹中数据\n",
    "* 目标：这次数据分析项目分析了豆瓣排名前250的电影来分析大众都喜欢的电影类型，帮助电影行业发展"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 定义css样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "/* 本电子讲义使用之CSS */\n",
       "div.code_cell {\n",
       "    background-color: #fceae6\n",
       "}\n",
       "div.cell.selected {\n",
       "    background-color: #e6eefe;\n",
       "    font-size: 2rem;\n",
       "    line-height: 2.4rem;\n",
       "}\n",
       "div.cell.selected .rendered_html table {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html pre code {\n",
       "    background-color: #C4E4ff;   \n",
       "    padding: 2px 25px;\n",
       "}\n",
       ".rendered_html pre {\n",
       "    background-color: #99c9ff;\n",
       "}\n",
       "div.code_cell .CodeMirror {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html img, .rendered_html svg {\n",
       "    max-width: 60%;\n",
       "    height: auto;\n",
       "    float: right;\n",
       "}\n",
       "\n",
       ".rendered_html img[src*=\"#full\"], .rendered_html svg[src*=\"#full\"] {\n",
       "    max-width: 95%;\n",
       "    height: auto;\n",
       "}\n",
       "\n",
       ".rendered_html img[src*=\"#thumbnail\"], .rendered_html svg[src*=\"#thumbnail\"] {\n",
       "    max-width: 15%;\n",
       "    height: auto;\n",
       "}\n",
       "\n",
       "/* Gradient transparent - color - transparent */\n",
       "hr {\n",
       "    border: 0;\n",
       "    border-bottom: 1px dashed #ccc;\n",
       "}\n",
       ".emoticon{\n",
       "    font-size: 5rem;\n",
       "    line-height: 4.4rem;\n",
       "    text-align: center;\n",
       "    vertical-align: middle;\n",
       "}\n",
       ".bg-split_apply_comine {\n",
       "    width: 500px;     \n",
       "    height: 300px;\n",
       "    background: url('02_split-apply-comine_500x300.png') -10px -10px;\n",
       "    float: right;\n",
       "}\n",
       ".bg-comine {\n",
       "    width: 175px;\n",
       "    height: 150px;\n",
       "    background: url('02_split-apply-comine_500x300.png') -280px -80px;\n",
       "    float: right;\n",
       "}\n",
       ".bg-apply {\n",
       "    width: 155px;\n",
       "    height: 225px;\n",
       "    background: url('02_split-apply-comine_500x300.png') -160px -30px;\n",
       "    float: right;\n",
       "}\n",
       ".bg-split {\n",
       "    width: 205px;\n",
       "    height: 225px;\n",
       "    background: url('02_split-apply-comine_500x300.png') -10px -30px;\n",
       "    float: right;\n",
       "}\n",
       ".break {\n",
       "                   page-break-after: right; \n",
       "                   width:700px;\n",
       "                   clear:both;\n",
       "}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<style>\n",
    "/* 本电子讲义使用之CSS */\n",
    "div.code_cell {\n",
    "    background-color: #fceae6\n",
    "}\n",
    "div.cell.selected {\n",
    "    background-color: #e6eefe;\n",
    "    font-size: 2rem;\n",
    "    line-height: 2.4rem;\n",
    "}\n",
    "div.cell.selected .rendered_html table {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html pre code {\n",
    "    background-color: #C4E4ff;   \n",
    "    padding: 2px 25px;\n",
    "}\n",
    ".rendered_html pre {\n",
    "    background-color: #99c9ff;\n",
    "}\n",
    "div.code_cell .CodeMirror {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html img, .rendered_html svg {\n",
    "    max-width: 60%;\n",
    "    height: auto;\n",
    "    float: right;\n",
    "}\n",
    "\n",
    ".rendered_html img[src*=\"#full\"], .rendered_html svg[src*=\"#full\"] {\n",
    "    max-width: 95%;\n",
    "    height: auto;\n",
    "}\n",
    "\n",
    ".rendered_html img[src*=\"#thumbnail\"], .rendered_html svg[src*=\"#thumbnail\"] {\n",
    "    max-width: 15%;\n",
    "    height: auto;\n",
    "}\n",
    "\n",
    "/* Gradient transparent - color - transparent */\n",
    "hr {\n",
    "    border: 0;\n",
    "    border-bottom: 1px dashed #ccc;\n",
    "}\n",
    ".emoticon{\n",
    "    font-size: 5rem;\n",
    "    line-height: 4.4rem;\n",
    "    text-align: center;\n",
    "    vertical-align: middle;\n",
    "}\n",
    ".bg-split_apply_comine {\n",
    "    width: 500px;     \n",
    "    height: 300px;\n",
    "    background: url('02_split-apply-comine_500x300.png') -10px -10px;\n",
    "    float: right;\n",
    "}\n",
    ".bg-comine {\n",
    "    width: 175px;\n",
    "    height: 150px;\n",
    "    background: url('02_split-apply-comine_500x300.png') -280px -80px;\n",
    "    float: right;\n",
    "}\n",
    ".bg-apply {\n",
    "    width: 155px;\n",
    "    height: 225px;\n",
    "    background: url('02_split-apply-comine_500x300.png') -160px -30px;\n",
    "    float: right;\n",
    "}\n",
    ".bg-split {\n",
    "    width: 205px;\n",
    "    height: 225px;\n",
    "    background: url('02_split-apply-comine_500x300.png') -10px -30px;\n",
    "    float: right;\n",
    "}\n",
    ".break {\n",
    "                   page-break-after: right; \n",
    "                   width:700px;\n",
    "                   clear:both;\n",
    "}\n",
    "</style>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pandas数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 准备工作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "from flask import Flask,render_template"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly as py\n",
    "import  plotly.graph_objects as go\n",
    "import seaborn as sns\n",
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import time\n",
    "from statsmodels.stats.anova import anova_lm\n",
    "from statsmodels.formula.api import ols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_data():\n",
    "    return pd.read_csv('./datas/movielens-1m/users.dat',\n",
    "                      sep=\"::\",\n",
    "                      engine=\"python\",\n",
    "                      header=None,\n",
    "                      names=\"UserID::Gender::Age::Occupation::Zip-code\".split(\"::\")\n",
    "                      )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UserID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Zip-code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>48067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>56</td>\n",
       "      <td>16</td>\n",
       "      <td>70072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>15</td>\n",
       "      <td>55117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "      <td>02460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>55455</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   UserID Gender  Age  Occupation Zip-code\n",
       "0       1      F    1          10    48067\n",
       "1       2      M   56          16    70072\n",
       "2       3      M   25          15    55117\n",
       "3       4      M   45           7    02460\n",
       "4       5      M   25          20    55455"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = read_data()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<table border=\"1\" class=\"dataframe\">\\n  <thead>\\n    <tr style=\"text-align: right;\">\\n      <th></th>\\n      <th>UserID</th>\\n      <th>Gender</th>\\n      <th>Age</th>\\n      <th>Occupation</th>\\n      <th>Zip-code</th>\\n    </tr>\\n  </thead>\\n  <tbody>\\n    <tr>\\n      <th>1</th>\\n      <td>2</td>\\n      <td>M</td>\\n      <td>56</td>\\n      <td>16</td>\\n      <td>70072</td>\\n    </tr>\\n    <tr>\\n      <th>2</th>\\n      <td>3</td>\\n      <td>M</td>\\n      <td>25</td>\\n      <td>15</td>\\n      <td>55117</td>\\n    </tr>\\n    <tr>\\n      <th>3</th>\\n      <td>4</td>\\n      <td>M</td>\\n      <td>45</td>\\n      <td>7</td>\\n      <td>02460</td>\\n    </tr>\\n    <tr>\\n      <th>4</th>\\n      <td>5</td>\\n      <td>M</td>\\n      <td>25</td>\\n      <td>20</td>\\n      <td>55455</td>\\n    </tr>\\n    <tr>\\n      <th>6</th>\\n      <td>7</td>\\n      <td>M</td>\\n      <td>35</td>\\n      <td>1</td>\\n      <td>06810</td>\\n    </tr>\\n  </tbody>\\n</table>'"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Gender']=='M'].head().to_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_data_2():\n",
    "    return pd.read_csv('./datas/movielens-1m/movies.dat',\n",
    "                      sep=\"::\",\n",
    "                      engine=\"python\",\n",
    "                      header=None,\n",
    "                      names=\"序号::电影名称::电影类型\".split(\"::\")\n",
    "                      )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>序号</th>\n",
       "      <th>电影名称</th>\n",
       "      <th>电影类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Animation|Children's|Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>Adventure|Children's|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   序号                                电影名称                          电影类型\n",
       "0   1                    Toy Story (1995)   Animation|Children's|Comedy\n",
       "1   2                      Jumanji (1995)  Adventure|Children's|Fantasy\n",
       "2   3             Grumpier Old Men (1995)                Comedy|Romance\n",
       "3   4            Waiting to Exhale (1995)                  Comedy|Drama\n",
       "4   5  Father of the Bride Part II (1995)                        Comedy"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = read_data_2()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([\"Animation|Children's|Comedy\", \"Adventure|Children's|Fantasy\",\n",
       "       'Comedy|Romance', 'Comedy|Drama', 'Comedy',\n",
       "       'Action|Crime|Thriller', \"Adventure|Children's\", 'Action',\n",
       "       'Action|Adventure|Thriller', 'Comedy|Drama|Romance',\n",
       "       'Comedy|Horror', \"Animation|Children's\", 'Drama',\n",
       "       'Action|Adventure|Romance', 'Drama|Thriller', 'Drama|Romance',\n",
       "       'Thriller', 'Action|Comedy|Drama', 'Crime|Drama|Thriller',\n",
       "       'Drama|Sci-Fi', 'Romance', 'Adventure|Sci-Fi', 'Adventure|Romance',\n",
       "       \"Children's|Comedy|Drama\", 'Documentary', 'Drama|War',\n",
       "       'Action|Crime|Drama', 'Action|Adventure', 'Crime|Thriller',\n",
       "       \"Animation|Children's|Musical|Romance\", 'Action|Drama|Thriller',\n",
       "       \"Children's|Comedy\", 'Drama|Mystery', 'Sci-Fi|Thriller',\n",
       "       'Action|Comedy|Crime|Horror|Thriller', 'Drama|Musical',\n",
       "       'Crime|Drama|Romance', 'Adventure|Drama', 'Action|Thriller',\n",
       "       \"Adventure|Children's|Comedy|Musical\", 'Action|Drama|War',\n",
       "       'Action|Adventure|Crime', 'Crime', 'Drama|Mystery|Romance',\n",
       "       'Action|Drama', 'Drama|Romance|War', 'Horror',\n",
       "       'Action|Adventure|Comedy|Crime', 'Comedy|War',\n",
       "       'Action|Adventure|Mystery|Sci-Fi', 'Drama|Thriller|War',\n",
       "       'Action|Romance|Thriller', 'Crime|Film-Noir|Mystery|Thriller',\n",
       "       'Action|Adventure|Drama|Romance', \"Adventure|Children's|Drama\",\n",
       "       'Action|Sci-Fi|Thriller', 'Action|Adventure|Sci-Fi',\n",
       "       \"Action|Children's\", 'Horror|Sci-Fi', 'Action|Crime|Sci-Fi',\n",
       "       'Western', \"Animation|Children's|Comedy|Romance\",\n",
       "       \"Children's|Drama\", 'Crime|Drama',\n",
       "       'Drama|Fantasy|Romance|Thriller', 'Drama|Horror', 'Comedy|Sci-Fi',\n",
       "       'Mystery|Thriller', \"Adventure|Children's|Comedy|Fantasy|Romance\",\n",
       "       'Action|Adventure|Fantasy|Sci-Fi', 'Drama|Romance|War|Western',\n",
       "       'Action|Crime', 'Crime|Drama|Romance|Thriller',\n",
       "       'Action|Adventure|Western', 'Horror|Thriller',\n",
       "       \"Children's|Comedy|Fantasy\", 'Film-Noir|Thriller',\n",
       "       'Action|Comedy|Musical|Sci-Fi', \"Children's\",\n",
       "       'Drama|Mystery|Thriller', 'Comedy|Romance|War', 'Action|Comedy',\n",
       "       \"Adventure|Children's|Romance\", \"Animation|Children's|Musical\",\n",
       "       'Comedy|Crime|Fantasy', 'Action|Comedy|Western', 'Action|Sci-Fi',\n",
       "       'Action|Adventure|Comedy|Romance', 'Comedy|Crime|Drama',\n",
       "       'Comedy|Thriller', 'Horror|Sci-Fi|Thriller',\n",
       "       'Mystery|Romance|Thriller', 'Comedy|Western', 'Drama|Western',\n",
       "       'Action|Adventure|Crime|Thriller', 'Action|Comedy|War',\n",
       "       'Comedy|Mystery', 'Comedy|Mystery|Romance', 'Comedy|Drama|War',\n",
       "       'Action|Drama|Mystery', 'Comedy|Crime|Horror', 'Film-Noir|Sci-Fi',\n",
       "       'Comedy|Romance|Thriller', \"Action|Adventure|Children's|Sci-Fi\",\n",
       "       \"Children's|Comedy|Musical\", 'Action|Adventure|Comedy',\n",
       "       'Action|Crime|Romance',\n",
       "       \"Action|Adventure|Animation|Children's|Fantasy\",\n",
       "       \"Animation|Children's|Comedy|Musical\", 'Adventure|Drama|Western',\n",
       "       'Action|Adventure|Crime|Drama',\n",
       "       'Action|Adventure|Animation|Horror|Sci-Fi', 'Action|Horror|Sci-Fi',\n",
       "       'War', 'Action|Adventure|Mystery', 'Mystery',\n",
       "       'Action|Adventure|Fantasy',\n",
       "       \"Adventure|Animation|Children's|Comedy|Fantasy\", 'Sci-Fi',\n",
       "       'Documentary|Drama', 'Action|Adventure|Comedy|War',\n",
       "       'Crime|Film-Noir|Thriller', 'Animation',\n",
       "       'Action|Adventure|Romance|Thriller', 'Animation|Sci-Fi',\n",
       "       'Animation|Comedy|Thriller', 'Film-Noir', 'Sci-Fi|War',\n",
       "       'Adventure', 'Comedy|Crime', 'Action|Sci-Fi|War',\n",
       "       'Comedy|Fantasy|Romance|Sci-Fi', 'Fantasy',\n",
       "       'Action|Mystery|Thriller', 'Comedy|Musical',\n",
       "       'Action|Adventure|Sci-Fi|Thriller', \"Children's|Drama|Fantasy\",\n",
       "       'Adventure|War', 'Musical|Romance', 'Comedy|Musical|Romance',\n",
       "       'Comedy|Mystery|Romance|Thriller', 'Film-Noir|Mystery', 'Musical',\n",
       "       \"Adventure|Children's|Drama|Musical\",\n",
       "       'Drama|Mystery|Sci-Fi|Thriller', 'Romance|Thriller',\n",
       "       'Film-Noir|Romance|Thriller', 'Crime|Film-Noir|Mystery',\n",
       "       'Adventure|Comedy', 'Action|Adventure|Romance|War', 'Romance|War',\n",
       "       'Action|Drama|Western', \"Children's|Comedy|Western\",\n",
       "       \"Adventure|Children's|Comedy\", \"Children's|Comedy|Mystery\",\n",
       "       \"Adventure|Children's|Fantasy|Sci-Fi\",\n",
       "       \"Adventure|Animation|Children's|Musical\",\n",
       "       \"Adventure|Children's|Musical\", 'Crime|Film-Noir',\n",
       "       \"Adventure|Children's|Comedy|Fantasy\",\n",
       "       \"Children's|Drama|Fantasy|Sci-Fi\", 'Action|Romance',\n",
       "       'Adventure|Western', 'Comedy|Fantasy', 'Animation|Comedy',\n",
       "       'Crime|Drama|Film-Noir', 'Action|Adventure|Drama|Sci-Fi|War',\n",
       "       'Action|Sci-Fi|Thriller|War', 'Action|Western',\n",
       "       \"Action|Animation|Children's|Sci-Fi|Thriller|War\",\n",
       "       'Action|Adventure|Romance|Sci-Fi|War',\n",
       "       'Action|Horror|Sci-Fi|Thriller',\n",
       "       'Action|Adventure|Comedy|Horror|Sci-Fi', 'Action|Comedy|Musical',\n",
       "       'Mystery|Sci-Fi', 'Film-Noir|Mystery|Thriller',\n",
       "       'Adventure|Comedy|Drama', 'Action|Adventure|Comedy|Horror',\n",
       "       'Action|Drama|Mystery|Romance|Thriller', 'Comedy|Mystery|Thriller',\n",
       "       'Adventure|Animation|Sci-Fi|Thriller', 'Action|Drama|Romance',\n",
       "       'Action|Adventure|Drama', 'Comedy|Drama|Musical',\n",
       "       'Documentary|War', 'Drama|Musical|War', 'Action|Horror',\n",
       "       'Horror|Romance', 'Action|Comedy|Sci-Fi|War', 'Crime|Drama|Sci-Fi',\n",
       "       'Action|Romance|War', 'Action|Comedy|Crime|Drama',\n",
       "       'Action|Drama|Thriller|War', \"Action|Adventure|Children's\",\n",
       "       \"Action|Adventure|Children's|Fantasy\",\n",
       "       \"Adventure|Animation|Children's|Comedy|Musical\",\n",
       "       'Crime|Drama|Mystery', 'Action|Adventure|Comedy|Sci-Fi',\n",
       "       \"Children's|Fantasy\", 'Action|Mystery|Sci-Fi|Thriller',\n",
       "       'Action|Mystery|Romance|Thriller', 'Adventure|Thriller',\n",
       "       'Action|Thriller|War', 'Action|Crime|Mystery',\n",
       "       'Horror|Mystery|Thriller', 'Crime|Horror|Mystery|Thriller',\n",
       "       'Comedy|Drama|Thriller', 'Drama|Sci-Fi|Thriller',\n",
       "       'Drama|Romance|Thriller', 'Action|Adventure|Sci-Fi|War',\n",
       "       'Comedy|Crime|Drama|Mystery', 'Comedy|Crime|Mystery|Thriller',\n",
       "       'Film-Noir|Sci-Fi|Thriller', 'Adventure|Sci-Fi|Thriller',\n",
       "       'Crime|Drama|Mystery|Thriller', 'Comedy|Documentary',\n",
       "       'Documentary|Musical', 'Action|Drama|Sci-Fi|Thriller',\n",
       "       \"Adventure|Animation|Children's|Fantasy\",\n",
       "       'Adventure|Comedy|Romance', 'Mystery|Sci-Fi|Thriller',\n",
       "       'Action|Comedy|Crime', \"Animation|Children's|Fantasy|War\",\n",
       "       'Action|Crime|Drama|Thriller', 'Comedy|Sci-Fi|Western',\n",
       "       \"Children's|Fantasy|Musical\", 'Fantasy|Sci-Fi',\n",
       "       \"Children's|Comedy|Sci-Fi\", \"Action|Adventure|Children's|Comedy\",\n",
       "       \"Adventure|Children's|Drama|Romance\",\n",
       "       \"Adventure|Children's|Sci-Fi\",\n",
       "       \"Adventure|Children's|Comedy|Fantasy|Sci-Fi\",\n",
       "       \"Animation|Children's|Comedy|Musical|Romance\",\n",
       "       \"Children's|Musical\", 'Drama|Fantasy',\n",
       "       \"Animation|Children's|Fantasy|Musical\", 'Adventure|Comedy|Musical',\n",
       "       \"Children's|Sci-Fi\", \"Children's|Horror\", 'Comedy|Fantasy|Romance',\n",
       "       'Comedy|Crime|Thriller', \"Adventure|Animation|Children's|Sci-Fi\",\n",
       "       'Action|Crime|Mystery|Thriller', 'Adventure|Musical',\n",
       "       \"Animation|Children's|Drama|Fantasy\", \"Children's|Fantasy|Sci-Fi\",\n",
       "       'Adventure|Fantasy|Romance', 'Crime|Horror',\n",
       "       'Action|Adventure|Horror', 'Adventure|Fantasy|Sci-Fi',\n",
       "       'Drama|Film-Noir|Thriller', 'Action|Comedy|Fantasy',\n",
       "       'Sci-Fi|Thriller|War', 'Action|Adventure|Sci-Fi|Thriller|War',\n",
       "       'Action|Adventure|Drama|Thriller', 'Crime|Horror|Thriller',\n",
       "       'Animation|Musical', 'Action|War',\n",
       "       'Action|Comedy|Romance|Thriller', 'Comedy|Horror|Thriller',\n",
       "       'Drama|Horror|Thriller', 'Action|Sci-Fi|Thriller|Western',\n",
       "       'Drama|Romance|Sci-Fi', 'Action|Adventure|Horror|Thriller',\n",
       "       'Comedy|Film-Noir|Thriller', 'Comedy|Horror|Musical|Sci-Fi',\n",
       "       'Comedy|Romance|Sci-Fi', 'Action|Comedy|Sci-Fi|Thriller',\n",
       "       'Action|Sci-Fi|Western', 'Comedy|Horror|Musical', 'Crime|Mystery',\n",
       "       'Animation|Mystery', 'Action|Horror|Thriller',\n",
       "       'Action|Drama|Fantasy|Romance', 'Horror|Mystery',\n",
       "       \"Adventure|Animation|Children's\", 'Musical|Romance|War',\n",
       "       'Adventure|Drama|Romance', 'Adventure|Animation|Film-Noir',\n",
       "       'Action|Adventure|Animation', 'Comedy|Drama|Western',\n",
       "       'Adventure|Comedy|Sci-Fi', 'Drama|Romance|Western',\n",
       "       'Comedy|Drama|Sci-Fi', 'Action|Drama|Romance|Thriller',\n",
       "       'Adventure|Romance|Sci-Fi', 'Film-Noir|Horror',\n",
       "       'Crime|Drama|Film-Noir|Thriller', 'Action|Adventure|War',\n",
       "       'Romance|Western', \"Action|Children's|Fantasy\",\n",
       "       'Adventure|Drama|Thriller', 'Adventure|Fantasy', 'Musical|War',\n",
       "       'Adventure|Musical|Romance', 'Action|Romance|Sci-Fi',\n",
       "       'Drama|Film-Noir', 'Comedy|Horror|Sci-Fi',\n",
       "       'Adventure|Drama|Romance|Sci-Fi', 'Adventure|Animation|Sci-Fi',\n",
       "       'Adventure|Crime|Sci-Fi|Thriller'], dtype=object)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.unique(df['电影类型'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        Animation|Children's|Comedy\n",
       "1       Adventure|Children's|Fantasy\n",
       "2                     Comedy|Romance\n",
       "3                       Comedy|Drama\n",
       "4                             Comedy\n",
       "                    ...             \n",
       "3878                          Comedy\n",
       "3879                           Drama\n",
       "3880                           Drama\n",
       "3881                           Drama\n",
       "3882                  Drama|Thriller\n",
       "Name: 电影类型, Length: 3883, dtype: object"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['电影类型']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        Animation|Children's|Comedy\n",
       "1       Adventure|Children's|Fantasy\n",
       "2                     Comedy|Romance\n",
       "3                       Comedy|Drama\n",
       "4                             Comedy\n",
       "                    ...             \n",
       "3878                          Comedy\n",
       "3879                           Drama\n",
       "3880                           Drama\n",
       "3881                           Drama\n",
       "3882                  Drama|Thriller\n",
       "Name: 电影类型, Length: 3883, dtype: object"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_category = df['电影类型']\n",
    "movies_category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Drama',\n",
       " 'Action',\n",
       " 'Thriller',\n",
       " 'Fantasy',\n",
       " 'Crime',\n",
       " 'Western',\n",
       " 'Romance',\n",
       " 'Mystery',\n",
       " 'Horror',\n",
       " 'Musical',\n",
       " 'Film-Noir',\n",
       " 'Adventure',\n",
       " 'Documentary',\n",
       " 'War',\n",
       " 'Animation',\n",
       " \"Children's\",\n",
       " 'Sci-Fi',\n",
       " 'Comedy']"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 电影类型总览\n",
    "m_category = [i.split('|')for i in movies_category]\n",
    "m_category = [j for i in m_category for j in i]\n",
    "m_category_list = list(set(m_category))\n",
    "m_category_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(m_category_list) #共有18种电影类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>序号</th>\n",
       "      <th>电影名称</th>\n",
       "      <th>电影类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Animation|Children's|Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Balto (1995)</td>\n",
       "      <td>Animation|Children's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>Pocahontas (1995)</td>\n",
       "      <td>Animation|Children's|Musical|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>239</td>\n",
       "      <td>Goofy Movie, A (1995)</td>\n",
       "      <td>Animation|Children's|Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>244</td>\n",
       "      <td>Gumby: The Movie (1995)</td>\n",
       "      <td>Animation|Children's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3690</th>\n",
       "      <td>3759</td>\n",
       "      <td>Fun and Fancy Free (1947)</td>\n",
       "      <td>Animation|Children's|Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3706</th>\n",
       "      <td>3775</td>\n",
       "      <td>Make Mine Music (1946)</td>\n",
       "      <td>Animation|Children's|Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3707</th>\n",
       "      <td>3776</td>\n",
       "      <td>Melody Time (1948)</td>\n",
       "      <td>Animation|Children's|Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3730</th>\n",
       "      <td>3799</td>\n",
       "      <td>Pok�mon the Movie 2000 (2000)</td>\n",
       "      <td>Animation|Children's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3875</th>\n",
       "      <td>3945</td>\n",
       "      <td>Digimon: The Movie (2000)</td>\n",
       "      <td>Adventure|Animation|Children's</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>105 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        序号                           电影名称  \\\n",
       "0        1               Toy Story (1995)   \n",
       "12      13                   Balto (1995)   \n",
       "47      48              Pocahontas (1995)   \n",
       "236    239          Goofy Movie, A (1995)   \n",
       "241    244        Gumby: The Movie (1995)   \n",
       "...    ...                            ...   \n",
       "3690  3759      Fun and Fancy Free (1947)   \n",
       "3706  3775         Make Mine Music (1946)   \n",
       "3707  3776             Melody Time (1948)   \n",
       "3730  3799  Pok�mon the Movie 2000 (2000)   \n",
       "3875  3945      Digimon: The Movie (2000)   \n",
       "\n",
       "                                      电影类型  \n",
       "0              Animation|Children's|Comedy  \n",
       "12                    Animation|Children's  \n",
       "47    Animation|Children's|Musical|Romance  \n",
       "236    Animation|Children's|Comedy|Romance  \n",
       "241                   Animation|Children's  \n",
       "...                                    ...  \n",
       "3690          Animation|Children's|Musical  \n",
       "3706          Animation|Children's|Musical  \n",
       "3707          Animation|Children's|Musical  \n",
       "3730                  Animation|Children's  \n",
       "3875        Adventure|Animation|Children's  \n",
       "\n",
       "[105 rows x 3 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['电影类型'].str.contains('Animation')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>序号</th>\n",
       "      <th>电影名称</th>\n",
       "      <th>电影类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Animation|Children's|Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>Adventure|Children's|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Tom and Huck (1995)</td>\n",
       "      <td>Adventure|Children's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Balto (1995)</td>\n",
       "      <td>Animation|Children's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Babe (1995)</td>\n",
       "      <td>Children's|Comedy|Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3706</th>\n",
       "      <td>3775</td>\n",
       "      <td>Make Mine Music (1946)</td>\n",
       "      <td>Animation|Children's|Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3707</th>\n",
       "      <td>3776</td>\n",
       "      <td>Melody Time (1948)</td>\n",
       "      <td>Animation|Children's|Musical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3730</th>\n",
       "      <td>3799</td>\n",
       "      <td>Pok�mon the Movie 2000 (2000)</td>\n",
       "      <td>Animation|Children's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3750</th>\n",
       "      <td>3820</td>\n",
       "      <td>Thomas and the Magic Railroad (2000)</td>\n",
       "      <td>Children's</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3875</th>\n",
       "      <td>3945</td>\n",
       "      <td>Digimon: The Movie (2000)</td>\n",
       "      <td>Adventure|Animation|Children's</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>251 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        序号                                  电影名称  \\\n",
       "0        1                      Toy Story (1995)   \n",
       "1        2                        Jumanji (1995)   \n",
       "7        8                   Tom and Huck (1995)   \n",
       "12      13                          Balto (1995)   \n",
       "33      34                           Babe (1995)   \n",
       "...    ...                                   ...   \n",
       "3706  3775                Make Mine Music (1946)   \n",
       "3707  3776                    Melody Time (1948)   \n",
       "3730  3799         Pok�mon the Movie 2000 (2000)   \n",
       "3750  3820  Thomas and the Magic Railroad (2000)   \n",
       "3875  3945             Digimon: The Movie (2000)   \n",
       "\n",
       "                                电影类型  \n",
       "0        Animation|Children's|Comedy  \n",
       "1       Adventure|Children's|Fantasy  \n",
       "7               Adventure|Children's  \n",
       "12              Animation|Children's  \n",
       "33           Children's|Comedy|Drama  \n",
       "...                              ...  \n",
       "3706    Animation|Children's|Musical  \n",
       "3707    Animation|Children's|Musical  \n",
       "3730            Animation|Children's  \n",
       "3750                      Children's  \n",
       "3875  Adventure|Animation|Children's  \n",
       "\n",
       "[251 rows x 3 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['电影类型'].str.contains('Children')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 导入清洗好的Animation表格，可视化分析该电影类型中电影上映年份与数量间关系\n",
    "df=pd.read_excel('.\\datas\\movielens-1m\\movie_year_Animation.xlsx') #导入Excel文件\n",
    "#折线图\n",
    "x =df['年份']                #x轴数据\n",
    "y=df['本类型电影数量']                 #y轴数据\n",
    "plt.plot(x,y,color='m',mfc='w')\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #解决中文乱码\n",
    "#图表标题\n",
    "plt.title('Animation类型电影数量与上映年份关系折线图')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comedy数据整理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>序号</th>\n",
       "      <th>电影名称</th>\n",
       "      <th>电影类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Animation|Children's|Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Sabrina (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3858</th>\n",
       "      <td>3928</td>\n",
       "      <td>Abbott and Costello Meet Frankenstein (1948)</td>\n",
       "      <td>Comedy|Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3859</th>\n",
       "      <td>3929</td>\n",
       "      <td>Bank Dick, The (1940)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3873</th>\n",
       "      <td>3943</td>\n",
       "      <td>Bamboozled (2000)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3874</th>\n",
       "      <td>3944</td>\n",
       "      <td>Bootmen (2000)</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3878</th>\n",
       "      <td>3948</td>\n",
       "      <td>Meet the Parents (2000)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1200 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        序号                                          电影名称  \\\n",
       "0        1                              Toy Story (1995)   \n",
       "2        3                       Grumpier Old Men (1995)   \n",
       "3        4                      Waiting to Exhale (1995)   \n",
       "4        5            Father of the Bride Part II (1995)   \n",
       "6        7                                Sabrina (1995)   \n",
       "...    ...                                           ...   \n",
       "3858  3928  Abbott and Costello Meet Frankenstein (1948)   \n",
       "3859  3929                         Bank Dick, The (1940)   \n",
       "3873  3943                             Bamboozled (2000)   \n",
       "3874  3944                                Bootmen (2000)   \n",
       "3878  3948                       Meet the Parents (2000)   \n",
       "\n",
       "                             电影类型  \n",
       "0     Animation|Children's|Comedy  \n",
       "2                  Comedy|Romance  \n",
       "3                    Comedy|Drama  \n",
       "4                          Comedy  \n",
       "6                  Comedy|Romance  \n",
       "...                           ...  \n",
       "3858                Comedy|Horror  \n",
       "3859                       Comedy  \n",
       "3873                       Comedy  \n",
       "3874                 Comedy|Drama  \n",
       "3878                       Comedy  \n",
       "\n",
       "[1200 rows x 3 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['电影类型'].str.contains('Comedy')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                         Toy Story (1995)\n",
       "1                           Jumanji (1995)\n",
       "2                  Grumpier Old Men (1995)\n",
       "3                 Waiting to Exhale (1995)\n",
       "4       Father of the Bride Part II (1995)\n",
       "                       ...                \n",
       "3878               Meet the Parents (2000)\n",
       "3879            Requiem for a Dream (2000)\n",
       "3880                      Tigerland (2000)\n",
       "3881               Two Family House (2000)\n",
       "3882                 Contender, The (2000)\n",
       "Name: 电影名称, Length: 3883, dtype: object"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_names = df['电影名称']\n",
    "movies_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "writer = pd.ExcelWriter('.\\datas\\movielens-1m\\movie_year_Comedy.xlsx')\n",
    "#columns参数的顺序就是excel的列顺序\n",
    "#df为需要保存的DataFrame\n",
    "df.to_excel(writer, index=False,encoding='utf-8',sheet_name='Comedy')\n",
    "#生成csv文件\n",
    "#df.to_csv(r'./1.csv',columns=['save1','save2'],index=False,sep=',')\n",
    "writer.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_excel('.\\datas\\movielens-1m\\movie_year_Comedy_01.xlsx') #导入Excel文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1996    327\n",
       "1995    321\n",
       "1998    305\n",
       "1997    298\n",
       "1999    265\n",
       "       ... \n",
       "Yao       1\n",
       "Todo      1\n",
       "L' A      1\n",
       "Hak       1\n",
       "L' �      1\n",
       "Name: 年份, Length: 305, dtype: int64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts=df['年份'].value_counts()\n",
    "counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plt.rcParams['font.sans-serif']=['SimHei'] #解决中文乱码\n",
    "# #折线图\n",
    "# x =df['年份']                #x轴数据\n",
    "# y=counts              #y轴数据\n",
    "# plt.plot(x,y,color='m',mfc='w')\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df=pd.read_excel('.\\datas\\movielens-1m\\movie_year_Comedy_01.xlsx') #导入Excel文件\n",
    "# #折线图\n",
    "# x =df['年份']                #x轴数据\n",
    "# y=df['电影名称']                 #y轴数据\n",
    "# plt.plot(x,y,color='b',mfc='w')\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 豆瓣top250+数据读取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "from flask import Flask,render_template\n",
    "import seaborn as sns\n",
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import time\n",
    "from statsmodels.stats.anova import anova_lm\n",
    "from statsmodels.formula.api import ols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>电影排名</th>\n",
       "      <th>电影名</th>\n",
       "      <th>年份</th>\n",
       "      <th>地区</th>\n",
       "      <th>剧情类型</th>\n",
       "      <th>导演</th>\n",
       "      <th>主演</th>\n",
       "      <th>评分</th>\n",
       "      <th>简介</th>\n",
       "      <th>评论人数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>1994</td>\n",
       "      <td>美国</td>\n",
       "      <td>犯罪 剧情</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>蒂姆·罗宾斯 Tim Robbins /</td>\n",
       "      <td>9.7</td>\n",
       "      <td>希望让人自由。</td>\n",
       "      <td>2075220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>中国大陆 中国香港</td>\n",
       "      <td>剧情 爱情 同性</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>张国荣 Leslie Cheung / 张丰毅 Fengyi Zha</td>\n",
       "      <td>9.6</td>\n",
       "      <td>风华绝代。</td>\n",
       "      <td>1538456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>美国</td>\n",
       "      <td>剧情 爱情</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>汤姆·汉克斯 Tom Hanks /</td>\n",
       "      <td>9.5</td>\n",
       "      <td>一部美国近现代史。</td>\n",
       "      <td>1568300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>1994</td>\n",
       "      <td>法国 美国</td>\n",
       "      <td>剧情 动作 犯罪</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 Jean Reno / 娜塔莉·波特曼</td>\n",
       "      <td>9.4</td>\n",
       "      <td>怪蜀黍和小萝莉不得不说的故事。</td>\n",
       "      <td>1759176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>美丽人生</td>\n",
       "      <td>1997</td>\n",
       "      <td>意大利</td>\n",
       "      <td>剧情 喜剧 爱情 战争</td>\n",
       "      <td>罗伯托·贝尼尼</td>\n",
       "      <td>罗伯托·贝尼尼 Roberto Beni</td>\n",
       "      <td>9.5</td>\n",
       "      <td>最美的谎言。</td>\n",
       "      <td>982948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>246</td>\n",
       "      <td>黑鹰坠落</td>\n",
       "      <td>2001</td>\n",
       "      <td>美国</td>\n",
       "      <td>动作 历史 战争</td>\n",
       "      <td>雷德利·斯科特</td>\n",
       "      <td>乔什·哈奈特 Josh Hartnett /</td>\n",
       "      <td>8.7</td>\n",
       "      <td>还原真实而残酷的战争。</td>\n",
       "      <td>212945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>247</td>\n",
       "      <td>四个春天</td>\n",
       "      <td>2017</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>纪录片 家庭</td>\n",
       "      <td>陆庆屹</td>\n",
       "      <td>陆运坤 Yunkun Lu / 李桂贤 Guixian Li /</td>\n",
       "      <td>8.9</td>\n",
       "      <td>来也匆匆去也匆匆，就这样风雨兼程。</td>\n",
       "      <td>120716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>248</td>\n",
       "      <td>网络谜踪</td>\n",
       "      <td>2018</td>\n",
       "      <td>美国 俄罗斯</td>\n",
       "      <td>剧情 犯罪 悬疑 惊悚</td>\n",
       "      <td>阿尼什·查甘蒂</td>\n",
       "      <td>约翰·赵 John Cho / 米切尔</td>\n",
       "      <td>8.6</td>\n",
       "      <td>该影片暂时无简介</td>\n",
       "      <td>387748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>249</td>\n",
       "      <td>发条橙</td>\n",
       "      <td>1971</td>\n",
       "      <td>英国 美国</td>\n",
       "      <td>犯罪 剧情 科幻</td>\n",
       "      <td>Stanley</td>\n",
       "      <td>Malcolm McDowell / Patrick Magee / Michael</td>\n",
       "      <td>8.6</td>\n",
       "      <td>我完全康复了。</td>\n",
       "      <td>283630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>250</td>\n",
       "      <td>黑客帝国2：重装上阵</td>\n",
       "      <td>2003</td>\n",
       "      <td>美国 澳大利亚</td>\n",
       "      <td>动作 科幻</td>\n",
       "      <td>Andy</td>\n",
       "      <td>基努·里维斯 Keanu Reeves</td>\n",
       "      <td>8.6</td>\n",
       "      <td>一个精彩的世界观正在缓缓建立。</td>\n",
       "      <td>261449</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     电影排名         电影名     年份           地区          剧情类型        导演  \\\n",
       "0       1      肖申克的救赎  1994           美国          犯罪 剧情  弗兰克·德拉邦特   \n",
       "1       2        霸王别姬  1993    中国大陆 中国香港       剧情 爱情 同性       陈凯歌   \n",
       "2       3        阿甘正传  1994           美国          剧情 爱情  罗伯特·泽米吉斯   \n",
       "3       4     这个杀手不太冷  1994        法国 美国       剧情 动作 犯罪     吕克·贝松   \n",
       "4       5        美丽人生  1997          意大利    剧情 喜剧 爱情 战争   罗伯托·贝尼尼   \n",
       "..    ...         ...    ...          ...           ...       ...   \n",
       "245   246        黑鹰坠落  2001           美国       动作 历史 战争   雷德利·斯科特   \n",
       "246   247        四个春天  2017         中国大陆         纪录片 家庭       陆庆屹   \n",
       "247   248        网络谜踪  2018       美国 俄罗斯    剧情 犯罪 悬疑 惊悚   阿尼什·查甘蒂   \n",
       "248   249         发条橙  1971        英国 美国       犯罪 剧情 科幻   Stanley   \n",
       "249   250  黑客帝国2：重装上阵  2003      美国 澳大利亚          动作 科幻      Andy   \n",
       "\n",
       "                                             主演   评分                 简介  \\\n",
       "0                          蒂姆·罗宾斯 Tim Robbins /  9.7            希望让人自由。   \n",
       "1            张国荣 Leslie Cheung / 张丰毅 Fengyi Zha  9.6              风华绝代。   \n",
       "2                            汤姆·汉克斯 Tom Hanks /  9.5          一部美国近现代史。   \n",
       "3                      让·雷诺 Jean Reno / 娜塔莉·波特曼  9.4    怪蜀黍和小萝莉不得不说的故事。   \n",
       "4                          罗伯托·贝尼尼 Roberto Beni  9.5             最美的谎言。   \n",
       "..                                          ...  ...                ...   \n",
       "245                      乔什·哈奈特 Josh Hartnett /  8.7        还原真实而残酷的战争。   \n",
       "246            陆运坤 Yunkun Lu / 李桂贤 Guixian Li /  8.9  来也匆匆去也匆匆，就这样风雨兼程。   \n",
       "247                         约翰·赵 John Cho / 米切尔  8.6           该影片暂时无简介   \n",
       "248  Malcolm McDowell / Patrick Magee / Michael  8.6            我完全康复了。   \n",
       "249                         基努·里维斯 Keanu Reeves  8.6    一个精彩的世界观正在缓缓建立。   \n",
       "\n",
       "        评论人数  \n",
       "0    2075220  \n",
       "1    1538456  \n",
       "2    1568300  \n",
       "3    1759176  \n",
       "4     982948  \n",
       "..       ...  \n",
       "245   212945  \n",
       "246   120716  \n",
       "247   387748  \n",
       "248   283630  \n",
       "249   261449  \n",
       "\n",
       "[250 rows x 10 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = \"./datas/豆瓣_top250.csv\"\n",
    "df = pd.read_csv(path)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      电影排名    电影名     年份     地区   剧情类型     导演     主演     评分     简介   评论人数\n",
       "0    False  False  False  False  False  False  False  False  False  False\n",
       "1    False  False  False  False  False  False  False  False  False  False\n",
       "2    False  False  False  False  False  False  False  False  False  False\n",
       "3    False  False  False  False  False  False  False  False  False  False\n",
       "4    False  False  False  False  False  False  False  False  False  False\n",
       "..     ...    ...    ...    ...    ...    ...    ...    ...    ...    ...\n",
       "245  False  False  False  False  False  False  False  False  False  False\n",
       "246  False  False  False  False  False  False  False  False  False  False\n",
       "247  False  False  False  False  False  False  False  False  False  False\n",
       "248  False  False  False  False  False  False  False  False  False  False\n",
       "249  False  False  False  False  False  False  False  False  False  False\n",
       "\n",
       "[250 rows x 10 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看缺失值\n",
    "df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "电影排名    0\n",
       "电影名     0\n",
       "年份      0\n",
       "地区      0\n",
       "剧情类型    0\n",
       "导演      0\n",
       "主演      2\n",
       "评分      0\n",
       "简介      0\n",
       "评论人数    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 评分数量和评分间关系图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      9.7\n",
       "1      9.6\n",
       "2      9.5\n",
       "3      9.4\n",
       "4      9.5\n",
       "      ... \n",
       "245    8.7\n",
       "246    8.9\n",
       "247    8.6\n",
       "248    8.6\n",
       "249    8.6\n",
       "Name: 评分, Length: 250, dtype: float64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['评分']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20ef28a9b20>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['评分'] = df['评分'].astype(np.float64)\n",
    "score = df['评分'].value_counts().sort_index()\n",
    "plt.figure(figsize = (8,5))\n",
    "#x、y轴标签\n",
    "plt.xlabel('电影评分')\n",
    "plt.ylabel('评分数量')\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #解决中文乱码\n",
    "#图表标题\n",
    "plt.title('电影评分与参与评分数关系柱状图')\n",
    "score.plot(kind = 'bar', color = 'c', width = 0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 电影排名与评分间关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '电影排名与评分间的关系')"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,8))\n",
    "plt.xlabel('电影评分')\n",
    "plt.ylabel('电影排名')\n",
    "plt.gca().invert_yaxis()\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #解决中文乱码\n",
    "plt.scatter(df['电影排名'], df['评分'],  color='g') #真实值散点图\n",
    "plt.title('电影排名与评分间的关系')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '各类电影评分数量情况')"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:214: RuntimeWarning:\n",
      "\n",
      "Glyph 160 missing from current font.\n",
      "\n",
      "D:\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:183: RuntimeWarning:\n",
      "\n",
      "Glyph 160 missing from current font.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_type = df['剧情类型'].str.split(' ',expand = True)\n",
    "tp1 = df_type.apply(pd.value_counts).fillna('0')\n",
    "tp1 = tp1.astype(np.int64)\n",
    "tp1['count'] = tp1.sum(axis = 1)\n",
    "tp1.sort_values('count', ascending = False, inplace = True)\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #解决中文乱码\n",
    "tp1['count'].plot.bar(figsize = (12,5), color = 'pink', legend = True)\n",
    "plt.title('各类电影评分数量情况')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>导演</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>克里斯托弗·诺兰</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>宫崎骏</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>史蒂文·斯皮尔伯格</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>李安</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>王家卫</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>邓肯·琼斯</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>李力持</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>马克·赫尔曼</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>尼克·卡索维茨</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>马丁·布莱斯</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>184 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0  count\n",
       "导演                 \n",
       "克里斯托弗·诺兰   7      7\n",
       "宫崎骏        7      7\n",
       "史蒂文·斯皮尔伯格  6      6\n",
       "李安         5      5\n",
       "王家卫        5      5\n",
       "...       ..    ...\n",
       "邓肯·琼斯      1      1\n",
       "李力持        1      1\n",
       "马克·赫尔曼     1      1\n",
       "尼克·卡索维茨    1      1\n",
       "马丁·布莱斯     1      1\n",
       "\n",
       "[184 rows x 2 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_director = df['导演'].str.split(' / ',expand = True)\n",
    "\n",
    "drt1 = df_director.apply(pd.value_counts).fillna('0')\n",
    "drt1['count'] = drt1.sum(axis = 1)\n",
    "\n",
    "drt1.index.name = '导演'\n",
    "display(drt1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "#统计出版国家的数量，并使用柱状图和饼状图进行描述\n",
    "\n",
    "def Statistical_nation():\n",
    "\n",
    "    Movie_info= pd.read_csv('datas/douban_movie_info2.0.csv')\n",
    "\n",
    "    Nations  = []\n",
    "\n",
    "    for nation in Movie_info['Region'].str.split('/'):\n",
    "\n",
    "        for nations in nation:\n",
    "\n",
    "            Nations.append(nations.strip())\n",
    "\n",
    "    ps = pd.Series(Nations)\n",
    "\n",
    "    df = pd.DataFrame(ps,columns=['Nation'])\n",
    "\n",
    "    df['Nation'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Title</th>\n",
       "      <th>Director</th>\n",
       "      <th>Screenwriter</th>\n",
       "      <th>Main_performer</th>\n",
       "      <th>Types</th>\n",
       "      <th>Region</th>\n",
       "      <th>Language</th>\n",
       "      <th>ShowTime</th>\n",
       "      <th>Film_length</th>\n",
       "      <th>Score</th>\n",
       "      <th>Rating_people</th>\n",
       "      <th>Watching_people</th>\n",
       "      <th>Wtsee_people</th>\n",
       "      <th>Comments_people</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>弗兰克·德拉邦特 / 斯蒂芬·金</td>\n",
       "      <td>蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿</td>\n",
       "      <td>剧情/犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>1994</td>\n",
       "      <td>142</td>\n",
       "      <td>9.7</td>\n",
       "      <td>1869808</td>\n",
       "      <td>2644926</td>\n",
       "      <td>271571</td>\n",
       "      <td>337952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐</td>\n",
       "      <td>剧情/爱情/同性</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>1993</td>\n",
       "      <td>171</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1373527</td>\n",
       "      <td>2075888</td>\n",
       "      <td>275105</td>\n",
       "      <td>272480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯</td>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>1994</td>\n",
       "      <td>142</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1426947</td>\n",
       "      <td>2265521</td>\n",
       "      <td>218521</td>\n",
       "      <td>217998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼</td>\n",
       "      <td>剧情/动作/犯罪</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语 / 意大利语 / 法语</td>\n",
       "      <td>1994</td>\n",
       "      <td>110</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1621799</td>\n",
       "      <td>2613822</td>\n",
       "      <td>236719</td>\n",
       "      <td>267223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>美丽人生</td>\n",
       "      <td>罗伯托·贝尼尼</td>\n",
       "      <td>温琴佐·切拉米 / 罗伯托·贝尼尼</td>\n",
       "      <td>罗伯托·贝尼尼 / 尼可莱塔·布拉斯基 / 乔治·坎塔里尼</td>\n",
       "      <td>剧情/喜剧/爱情/战争</td>\n",
       "      <td>意大利</td>\n",
       "      <td>意大利语 / 德语 / 英语</td>\n",
       "      <td>2020</td>\n",
       "      <td>116</td>\n",
       "      <td>9.5</td>\n",
       "      <td>907823</td>\n",
       "      <td>1286917</td>\n",
       "      <td>408504</td>\n",
       "      <td>187760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>245</td>\n",
       "      <td>梦之安魂曲</td>\n",
       "      <td>达伦·阿伦诺夫斯基</td>\n",
       "      <td>小胡伯特·塞尔比 / 达伦·阿伦诺夫斯基</td>\n",
       "      <td>艾伦·伯斯汀 / 杰瑞德·莱托 / 詹妮弗·康纳利</td>\n",
       "      <td>剧情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>2000</td>\n",
       "      <td>102</td>\n",
       "      <td>8.7</td>\n",
       "      <td>157321</td>\n",
       "      <td>210427</td>\n",
       "      <td>167391</td>\n",
       "      <td>42216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>246</td>\n",
       "      <td>变脸</td>\n",
       "      <td>吴宇森</td>\n",
       "      <td>麦克·韦柏 / 迈克尔·科拉里</td>\n",
       "      <td>约翰·特拉沃尔塔 / 尼古拉斯·凯奇 / 琼·艾伦</td>\n",
       "      <td>动作/科幻/惊悚/犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语 / 拉丁语</td>\n",
       "      <td>1997</td>\n",
       "      <td>138</td>\n",
       "      <td>8.5</td>\n",
       "      <td>303509</td>\n",
       "      <td>460719</td>\n",
       "      <td>84522</td>\n",
       "      <td>35592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>247</td>\n",
       "      <td>二十二</td>\n",
       "      <td>郭柯</td>\n",
       "      <td>无</td>\n",
       "      <td>无</td>\n",
       "      <td>纪录片</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>2017</td>\n",
       "      <td>99</td>\n",
       "      <td>8.7</td>\n",
       "      <td>199246</td>\n",
       "      <td>368169</td>\n",
       "      <td>159145</td>\n",
       "      <td>52294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>248</td>\n",
       "      <td>人生果实</td>\n",
       "      <td>原健之</td>\n",
       "      <td>无</td>\n",
       "      <td>津端修一 / 津端英子 / 树木希林</td>\n",
       "      <td>纪录片</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>2017</td>\n",
       "      <td>91</td>\n",
       "      <td>9.5</td>\n",
       "      <td>72740</td>\n",
       "      <td>92771</td>\n",
       "      <td>121496</td>\n",
       "      <td>27075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>249</td>\n",
       "      <td>四个春天</td>\n",
       "      <td>陆庆屹</td>\n",
       "      <td>无</td>\n",
       "      <td>陆运坤 / 李桂贤 / 陆庆伟 / 陆庆松 / 陆庆屹</td>\n",
       "      <td>纪录片 / 家庭</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>贵州独山话</td>\n",
       "      <td>2019</td>\n",
       "      <td>105</td>\n",
       "      <td>8.9</td>\n",
       "      <td>107290</td>\n",
       "      <td>147630</td>\n",
       "      <td>180634</td>\n",
       "      <td>42213</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0    Title   Director          Screenwriter  \\\n",
       "0             0   肖申克的救赎   弗兰克·德拉邦特      弗兰克·德拉邦特 / 斯蒂芬·金   \n",
       "1             1     霸王别姬        陈凯歌              芦苇 / 李碧华   \n",
       "2             2     阿甘正传   罗伯特·泽米吉斯      艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "3             3  这个杀手不太冷      吕克·贝松                 吕克·贝松   \n",
       "4             4     美丽人生    罗伯托·贝尼尼     温琴佐·切拉米 / 罗伯托·贝尼尼   \n",
       "..          ...      ...        ...                   ...   \n",
       "245         245    梦之安魂曲  达伦·阿伦诺夫斯基  小胡伯特·塞尔比 / 达伦·阿伦诺夫斯基   \n",
       "246         246       变脸        吴宇森       麦克·韦柏 / 迈克尔·科拉里   \n",
       "247         247      二十二         郭柯                     无   \n",
       "248         248     人生果实        原健之                     无   \n",
       "249         249     四个春天        陆庆屹                     无   \n",
       "\n",
       "                     Main_performer        Types        Region  \\\n",
       "0          蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿         剧情/犯罪            美国   \n",
       "1                   张国荣 / 张丰毅 / 巩俐      剧情/爱情/同性   中国大陆 / 中国香港   \n",
       "2          汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯         剧情/爱情            美国   \n",
       "3          让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼      剧情/动作/犯罪            法国   \n",
       "4    罗伯托·贝尼尼 / 尼可莱塔·布拉斯基 / 乔治·坎塔里尼   剧情/喜剧/爱情/战争           意大利   \n",
       "..                              ...          ...           ...   \n",
       "245      艾伦·伯斯汀 / 杰瑞德·莱托 / 詹妮弗·康纳利            剧情            美国   \n",
       "246      约翰·特拉沃尔塔 / 尼古拉斯·凯奇 / 琼·艾伦   动作/科幻/惊悚/犯罪            美国   \n",
       "247                               无          纪录片          中国大陆   \n",
       "248              津端修一 / 津端英子 / 树木希林          纪录片            日本   \n",
       "249     陆运坤 / 李桂贤 / 陆庆伟 / 陆庆松 / 陆庆屹     纪录片 / 家庭          中国大陆   \n",
       "\n",
       "            Language  ShowTime  Film_length  Score  Rating_people  \\\n",
       "0                 英语      1994          142    9.7        1869808   \n",
       "1              汉语普通话      1993          171    9.6        1373527   \n",
       "2                 英语      1994          142    9.5        1426947   \n",
       "3     英语 / 意大利语 / 法语      1994          110    9.4        1621799   \n",
       "4     意大利语 / 德语 / 英语      2020          116    9.5         907823   \n",
       "..               ...       ...          ...    ...            ...   \n",
       "245               英语      2000          102    8.7         157321   \n",
       "246         英语 / 拉丁语      1997          138    8.5         303509   \n",
       "247            汉语普通话      2017           99    8.7         199246   \n",
       "248               日语      2017           91    9.5          72740   \n",
       "249            贵州独山话      2019          105    8.9         107290   \n",
       "\n",
       "     Watching_people  Wtsee_people  Comments_people  \n",
       "0            2644926        271571           337952  \n",
       "1            2075888        275105           272480  \n",
       "2            2265521        218521           217998  \n",
       "3            2613822        236719           267223  \n",
       "4            1286917        408504           187760  \n",
       "..               ...           ...              ...  \n",
       "245           210427        167391            42216  \n",
       "246           460719         84522            35592  \n",
       "247           368169        159145            52294  \n",
       "248            92771        121496            27075  \n",
       "249           147630        180634            42213  \n",
       "\n",
       "[250 rows x 15 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Movie_info= pd.read_csv('datas/douban_movie_info2.0.csv')\n",
    "Movie_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>法国</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "       0     1    2     3    4    5    6    7    8    9    10   11\n",
       "0            美国  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "1          中国大陆    /  中国香港  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "2            美国  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "3            法国  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "4           意大利  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "..    ...   ...  ...   ...  ...  ...  ...  ...  ...  ...  ...  ...\n",
       "245          美国  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "246          美国  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "247  中国大陆   NaN  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "248    日本   NaN  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "249  中国大陆   NaN  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN\n",
       "\n",
       "[250 rows x 12 columns]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country =Movie_info['Region'].str.split(' ').apply(pd.Series)\n",
    "country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area1</th>\n",
       "      <th>area2</th>\n",
       "      <th>area3</th>\n",
       "      <th>area4</th>\n",
       "      <th>area5</th>\n",
       "      <th>area6</th>\n",
       "      <th>area7</th>\n",
       "      <th>area8</th>\n",
       "      <th>area9</th>\n",
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       "      <th>area11</th>\n",
       "      <th>area12</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>247</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>中国台湾</th>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>中国大陆</th>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国香港</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>丹麦</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>伊朗</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>俄罗斯</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <th>冰岛</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>加拿大</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>南非</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>印度</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>奥地利</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>巴西</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>希腊</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>德国</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>意大利</th>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>捷克</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新西兰</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日本</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>法国</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>波兰</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>泰国</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>澳大利亚</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱尔兰</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>瑞典</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>瑞士</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>美国</th>\n",
       "      <td>0</td>\n",
       "      <td>118</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>英国</th>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>荷兰</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>西班牙</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阿根廷</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阿联酋</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>韩国</th>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>黎巴嫩</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      area1  area2  area3  area4  area5  area6  area7  area8  area9  area10  \\\n",
       "        247      0      0      0      0      0      0      0      0       0   \n",
       "/         0      0     87      0     21      0      0      0      0       0   \n",
       "中国台湾      0      6      0      2      0      0      0      0      0       0   \n",
       "中国大陆      2     14      0      5      0      1      1      1      1       1   \n",
       "中国香港      0     18      0      8      0      0      0      0      0       0   \n",
       "丹麦        0      1      0      0      0      0      0      0      0       0   \n",
       "伊朗        0      2      0      0      0      0      0      0      0       0   \n",
       "俄罗斯       0      0      0      1      0      0      0      0      0       0   \n",
       "冰岛        0      0      0      0      0      0      0      0      0       0   \n",
       "加拿大       0      0      0      5      0      1      1      1      1       1   \n",
       "南非        0      0      0      1      0      1      1      1      1       1   \n",
       "印度        0      4      0      0      0      0      0      0      0       0   \n",
       "奥地利       0      0      0      1      0      0      0      0      0       0   \n",
       "巴西        0      1      0      0      0      1      1      1      1       1   \n",
       "希腊        0      0      0      1      0      0      0      0      0       0   \n",
       "德国        0      5      0     10      0      3      3      3      3       3   \n",
       "意大利       0      6      0      2      0      1      1      1      1       1   \n",
       "捷克        0      0      0      0      0      1      1      1      1       1   \n",
       "新西兰       0      1      0      2      0      0      0      0      0       0   \n",
       "日本        1     31      0      2      0      0      0      0      0       0   \n",
       "法国        0      8      0     10      0      1      1      1      1       1   \n",
       "波兰        0      0      0      0      0      0      0      0      0       0   \n",
       "泰国        0      1      0      0      0      0      0      0      0       0   \n",
       "澳大利亚      0      2      0      4      0      0      0      0      0       0   \n",
       "爱尔兰       0      1      0      0      0      0      0      0      0       0   \n",
       "瑞典        0      1      0      1      0      0      0      0      0       0   \n",
       "瑞士        0      0      0      3      0      1      1      1      1       1   \n",
       "美国        0    118      0     13      0      3      3      3      3       3   \n",
       "英国        0     14      0     15      0      4      4      4      4       4   \n",
       "荷兰        0      0      0      0      0      0      0      0      0       0   \n",
       "西班牙       0      1      0      1      0      2      2      2      2       2   \n",
       "阿根廷       0      1      0      0      0      0      0      0      0       0   \n",
       "阿联酋       0      0      0      0      0      0      0      0      0       0   \n",
       "韩国        0     10      0      0      0      1      1      1      1       1   \n",
       "黎巴嫩       0      1      0      0      0      0      0      0      0       0   \n",
       "\n",
       "      area11  area12  \n",
       "           0       0  \n",
       "/          0       0  \n",
       "中国台湾       0       0  \n",
       "中国大陆       1       1  \n",
       "中国香港       0       0  \n",
       "丹麦         0       0  \n",
       "伊朗         0       0  \n",
       "俄罗斯        0       0  \n",
       "冰岛         0       0  \n",
       "加拿大        1       1  \n",
       "南非         1       1  \n",
       "印度         0       0  \n",
       "奥地利        0       0  \n",
       "巴西         1       1  \n",
       "希腊         0       0  \n",
       "德国         3       3  \n",
       "意大利        1       1  \n",
       "捷克         1       1  \n",
       "新西兰        0       0  \n",
       "日本         0       0  \n",
       "法国         1       1  \n",
       "波兰         0       0  \n",
       "泰国         0       0  \n",
       "澳大利亚       0       0  \n",
       "爱尔兰        0       0  \n",
       "瑞典         0       0  \n",
       "瑞士         1       1  \n",
       "美国         3       3  \n",
       "英国         4       4  \n",
       "荷兰         0       0  \n",
       "西班牙        2       2  \n",
       "阿根廷        0       0  \n",
       "阿联酋        0       0  \n",
       "韩国         1       1  \n",
       "黎巴嫩        0       0  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_country = country.apply(pd.value_counts).fillna('0')\n",
    "all_country.columns = ['area1','area2','area3','area4','area5','area6','area7','area8','area9','area10','area11','area12']\n",
    "all_country['area1'] = all_country['area1'].astype(int)\n",
    "all_country['area2'] = all_country['area2'].astype(int)\n",
    "all_country['area3'] = all_country['area3'].astype(int)\n",
    "all_country['area4'] = all_country['area4'].astype(int)\n",
    "all_country['area5'] = all_country['area5'].astype(int)\n",
    "all_country['area6'] = all_country['area6'].astype(int)\n",
    "all_country['area7'] = all_country['area6'].astype(int)\n",
    "all_country['area8'] = all_country['area6'].astype(int)\n",
    "all_country['area9'] = all_country['area6'].astype(int)\n",
    "all_country['area10'] = all_country['area6'].astype(int)\n",
    "all_country['area11'] = all_country['area6'].astype(int)\n",
    "all_country['area12'] = all_country['area6'].astype(int)\n",
    "all_country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area1</th>\n",
       "      <th>area2</th>\n",
       "      <th>area3</th>\n",
       "      <th>area4</th>\n",
       "      <th>area5</th>\n",
       "      <th>area6</th>\n",
       "      <th>area7</th>\n",
       "      <th>area8</th>\n",
       "      <th>area9</th>\n",
       "      <th>area10</th>\n",
       "      <th>area11</th>\n",
       "      <th>area12</th>\n",
       "      <th>all_counts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>247</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>美国</th>\n",
       "      <td>0</td>\n",
       "      <td>118</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>/</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日本</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>英国</th>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    area1  area2  area3  area4  area5  area6  area7  area8  area9  area10  \\\n",
       "      247      0      0      0      0      0      0      0      0       0   \n",
       "美国      0    118      0     13      0      3      3      3      3       3   \n",
       "/       0      0     87      0     21      0      0      0      0       0   \n",
       "日本      1     31      0      2      0      0      0      0      0       0   \n",
       "英国      0     14      0     15      0      4      4      4      4       4   \n",
       "\n",
       "    area11  area12  all_counts  \n",
       "         0       0         247  \n",
       "美国       3       3         134  \n",
       "/        0       0         108  \n",
       "日本       0       0          34  \n",
       "英国       4       4          33  "
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_country['all_counts'] = all_country['area1']+all_country['area2']+all_country['area3']+all_country['area4']+all_country['area5']+all_country['area6']\n",
    "#降序\n",
    "all_country = all_country.sort_values(['all_counts'],ascending=False)\n",
    "all_country.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
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\"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"\\u8c46\\u74e3\\u7535\\u5f71Top250\\u4e2d\\u7684\\u4e0a\\u699c\\u7535\\u5f71\\u6240\\u5c5e\\u56fd\\u5bb6\\u6bd4\\u4f8b\"}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('e1ef8657-b8fd-491b-972d-3d90d5598cc9');\n",
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       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
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       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#数据可视化，饼状图\n",
    "\n",
    "Piedata = go.Pie(labels=Movie_info['Region'].value_counts().index,values=Movie_info['Region'].value_counts())\n",
    "Layout = go.Layout(title='豆瓣电影Top250中的上榜电影所属国家比例')\n",
    "fig = go.Figure(data=[Piedata],layout = Layout)\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
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     "metadata": {},
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   ],
   "source": [
    " #数据可视化-条形图\n",
    "Bardata = go.Bar(x=Movie_info['Region'].value_counts().index,y=Movie_info['Region'].value_counts(),marker=dict(color='steelblue'),opacity=0.5)\n",
    "\n",
    "Layout = go.Layout(title='豆瓣电影Top250中的上榜电影所属国家数量',xaxis=dict(title='国家',tickangle=45),yaxis=dict(title='数量'))\n",
    "\n",
    "fig = go.Figure(data=[Bardata],layout=Layout)\n",
    "\n",
    "fig"
   ]
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       "                        {\"responsive\": true}\n",
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       "                            \n",
       "var gd = document.getElementById('30c1c23c-2d21-44b6-a166-3123b8163c56');\n",
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       "            Plotly.purge(gd);\n",
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       "\n",
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       "var notebookContainer = gd.closest('#notebook-container');\n",
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       "    x.observe(notebookContainer, {childList: true});\n",
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       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
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       "\n",
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       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
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     },
     "metadata": {},
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   ],
   "source": [
    " #数据可视化-饼状图\n",
    "Piedata = go.Pie(labels=Movie_info['Types'].value_counts().index,values=Movie_info['Types'].value_counts())\n",
    "Layout = go.Layout(title='豆瓣电影Top250电影类型比例')\n",
    "fig = go.Figure(data=[Piedata],layout = Layout)\n",
    "fig"
   ]
  },
  {
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\"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"\\u8c46\\u74e3\\u7535\\u5f71Top250\\u7535\\u5f71\\u7c7b\\u578b\\u4e0e\\u6570\\u91cf\\u4e4b\\u95f4\\u5173\\u7cfb\\u67f1\\u72b6\\u56fe\"}, \"xaxis\": {\"tickangle\": 45, \"title\": {\"text\": \"\\u5267\\u60c5\\u7c7b\\u578b\"}}, \"yaxis\": {\"title\": {\"text\": \"\\u6570\\u91cf\"}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('31b056a7-fbf7-405c-849a-fdcefb825686');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    " #数据可视化-条形图\n",
    "Bardata = go.Bar(x=Movie_info['Types'].value_counts().index,y=Movie_info['Types'].value_counts(),marker=dict(color='steelblue'),opacity=0.5)\n",
    "\n",
    "Layout = go.Layout(title='豆瓣电影Top250电影类型与数量之间关系柱状图',xaxis=dict(title='剧情类型',tickangle=45),yaxis=dict(title='数量'))\n",
    "\n",
    "fig = go.Figure(data=[Bardata],layout=Layout)\n",
    "\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "  <tbody>\n",
       "    <tr>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>剧情/爱情/同性</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>剧情/爱情</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>剧情/动作/犯罪</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>剧情/喜剧/爱情/战争</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>剧情/爱情/灾难</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>剧情/动画/奇幻</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>剧情/历史/战争</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>剧情/科幻/悬疑/冒险</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>剧情</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             0    1    2\n",
       "0        剧情/犯罪  NaN  NaN\n",
       "1     剧情/爱情/同性  NaN  NaN\n",
       "2        剧情/爱情  NaN  NaN\n",
       "3     剧情/动作/犯罪  NaN  NaN\n",
       "4  剧情/喜剧/爱情/战争  NaN  NaN\n",
       "5     剧情/爱情/灾难  NaN  NaN\n",
       "6     剧情/动画/奇幻  NaN  NaN\n",
       "7     剧情/历史/战争  NaN  NaN\n",
       "8  剧情/科幻/悬疑/冒险  NaN  NaN\n",
       "9           剧情  NaN  NaN"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_type = Movie_info['Types'].str.split(' ').apply(pd.Series)\n",
    "all_type.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>tpye1</th>\n",
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       "      <th>all_counts</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>剧情</th>\n",
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       "      <th>剧情/家庭</th>\n",
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       "    <tr>\n",
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       "      <th>剧情/悬疑/惊悚/犯罪</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>纪录片</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>剧情/悬疑/惊悚</th>\n",
       "      <td>5</td>\n",
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       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tpye1  type2  type3  all_counts\n",
       "剧情              20      0      0          20\n",
       "剧情/爱情           15      0      0          15\n",
       "剧情/犯罪           15      0      0          15\n",
       "剧情/家庭            9      0      0           9\n",
       "动画/奇幻/冒险         9      0      0           9\n",
       "剧情/喜剧/爱情         8      0      0           8\n",
       "剧情/喜剧            6      0      0           6\n",
       "剧情/悬疑/惊悚/犯罪      6      0      0           6\n",
       "纪录片              5      0      0           5\n",
       "剧情/悬疑/惊悚         5      0      0           5"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_type = Movie_info['Types'].str.split(' ').apply(pd.Series)\n",
    "all_type = all_type.apply(pd.value_counts).fillna('0')\n",
    "all_type.columns = ['tpye1','type2','type3']\n",
    "all_type['tpye1'] = all_type['tpye1'].astype(int)\n",
    "all_type['type2'] = all_type['type2'].astype(int)\n",
    "all_type['type3'] = all_type['type3'].astype(int)\n",
    "all_type.head(10)\n",
    "\n",
    "all_type['all_counts'] = all_type['tpye1']+all_type['type2']+all_type['type3']\n",
    "all_type = all_type.sort_values(['all_counts'],ascending=False)\n",
    "all_type.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tpye1  0     2.0\n",
       "       1    80.0\n",
       "       2    15.0\n",
       "       3     8.0\n",
       "       4     2.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_type = all_type.apply(pd.value_counts)\n",
    "all_type.unstack().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>剧情/犯罪</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>剧情/爱情/同性</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0    1    2\n",
       "0     剧情/犯罪  NaN  NaN\n",
       "1  剧情/爱情/同性  NaN  NaN"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_type =Movie_info['Types'].str.split(' ').apply(pd.Series)\n",
    "all_type.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0  /               NaN\n",
       "   剧情             20.0\n",
       "   剧情/传记           2.0\n",
       "   剧情/传记/历史        1.0\n",
       "   剧情/传记/历史/战争     1.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_type=all_type.apply(pd.value_counts)\n",
    "all_type.unstack().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Title</th>\n",
       "      <th>Director</th>\n",
       "      <th>Screenwriter</th>\n",
       "      <th>Main_performer</th>\n",
       "      <th>Types</th>\n",
       "      <th>Region</th>\n",
       "      <th>Language</th>\n",
       "      <th>ShowTime</th>\n",
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       "      <th>Score</th>\n",
       "      <th>Rating_people</th>\n",
       "      <th>Watching_people</th>\n",
       "      <th>Wtsee_people</th>\n",
       "      <th>Comments_people</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐</td>\n",
       "      <td>剧情/爱情/同性</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>1993</td>\n",
       "      <td>171</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1373527</td>\n",
       "      <td>2075888</td>\n",
       "      <td>275105</td>\n",
       "      <td>272480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>大话西游之大圣娶亲</td>\n",
       "      <td>刘镇伟</td>\n",
       "      <td>刘镇伟</td>\n",
       "      <td>周星驰 / 吴孟达 / 朱茵</td>\n",
       "      <td>喜剧/爱情/奇幻/古装</td>\n",
       "      <td>中国香港 / 中国大陆</td>\n",
       "      <td>粤语 / 汉语普通话</td>\n",
       "      <td>1995</td>\n",
       "      <td>95</td>\n",
       "      <td>9.2</td>\n",
       "      <td>992143</td>\n",
       "      <td>1621715</td>\n",
       "      <td>126432</td>\n",
       "      <td>150276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>无间道</td>\n",
       "      <td>刘伟强</td>\n",
       "      <td>麦兆辉 / 庄文强</td>\n",
       "      <td>刘德华 / 梁朝伟 / 黄秋生</td>\n",
       "      <td>剧情/悬疑/犯罪</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语</td>\n",
       "      <td>2002</td>\n",
       "      <td>101</td>\n",
       "      <td>9.2</td>\n",
       "      <td>811448</td>\n",
       "      <td>1341575</td>\n",
       "      <td>158992</td>\n",
       "      <td>109866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>活着</td>\n",
       "      <td>张艺谋</td>\n",
       "      <td>芦苇 / 余华</td>\n",
       "      <td>葛优 / 巩俐 / 姜武</td>\n",
       "      <td>剧情/家庭/历史</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>1994</td>\n",
       "      <td>132</td>\n",
       "      <td>9.2</td>\n",
       "      <td>526734</td>\n",
       "      <td>779096</td>\n",
       "      <td>272885</td>\n",
       "      <td>101208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>少年派的奇幻漂流</td>\n",
       "      <td>李安</td>\n",
       "      <td>扬·马特尔 / 大卫·麦基</td>\n",
       "      <td>苏拉·沙玛 / 伊尔凡·可汗 / 拉菲·斯波</td>\n",
       "      <td>剧情/奇幻/冒险</td>\n",
       "      <td>美国 / 中国台湾 / 英国 / 加拿大</td>\n",
       "      <td>美国 / 中国台湾 / 英国 / 加拿大</td>\n",
       "      <td>2012</td>\n",
       "      <td>127</td>\n",
       "      <td>9.1</td>\n",
       "      <td>971460</td>\n",
       "      <td>1495187</td>\n",
       "      <td>194292</td>\n",
       "      <td>216602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>末代皇帝</td>\n",
       "      <td>贝纳尔多·贝托鲁奇</td>\n",
       "      <td>贝纳尔多·贝托鲁奇 / 马克·派普罗</td>\n",
       "      <td>尊龙 / 陈冲 / 邬君梅</td>\n",
       "      <td>剧情/传记/历史</td>\n",
       "      <td>英国 / 意大利 / 中国大陆 / 法国</td>\n",
       "      <td>英语 / 汉语普通话 / 日语</td>\n",
       "      <td>1987</td>\n",
       "      <td>163</td>\n",
       "      <td>9.2</td>\n",
       "      <td>459153</td>\n",
       "      <td>698624</td>\n",
       "      <td>256309</td>\n",
       "      <td>89290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>36</td>\n",
       "      <td>鬼子来了</td>\n",
       "      <td>姜文</td>\n",
       "      <td>姜文 / 史建全 / 述平 / 尤凤伟</td>\n",
       "      <td>姜文 / 香川照之 / 袁丁</td>\n",
       "      <td>剧情/历史/战争</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话 / 日语 / 唐山话</td>\n",
       "      <td>2000</td>\n",
       "      <td>139</td>\n",
       "      <td>9.2</td>\n",
       "      <td>416646</td>\n",
       "      <td>631875</td>\n",
       "      <td>208134</td>\n",
       "      <td>71459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>大话西游之月光宝盒</td>\n",
       "      <td>刘镇伟</td>\n",
       "      <td>刘镇伟 / 吴承恩</td>\n",
       "      <td>周星驰 / 吴孟达 / 罗家英</td>\n",
       "      <td>喜剧/爱情/奇幻/古装</td>\n",
       "      <td>中国香港 / 中国大陆</td>\n",
       "      <td>粤语 / 汉语普通话</td>\n",
       "      <td>1995</td>\n",
       "      <td>87</td>\n",
       "      <td>9.0</td>\n",
       "      <td>799583</td>\n",
       "      <td>1426088</td>\n",
       "      <td>67887</td>\n",
       "      <td>71830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>53</td>\n",
       "      <td>我不是药神</td>\n",
       "      <td>文牧野</td>\n",
       "      <td>韩家女 / 钟伟 / 文牧野</td>\n",
       "      <td>徐峥 / 王传君 / 周一围</td>\n",
       "      <td>剧情/喜剧</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话 / 英语 / 上海话 / 印地语</td>\n",
       "      <td>2018</td>\n",
       "      <td>117</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1391409</td>\n",
       "      <td>4045012</td>\n",
       "      <td>852656</td>\n",
       "      <td>387322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>55</td>\n",
       "      <td>大闹天宫</td>\n",
       "      <td>万籁鸣</td>\n",
       "      <td>李克弱 / 万籁鸣</td>\n",
       "      <td>邱岳峰 / 富润生 / 毕克</td>\n",
       "      <td>动画/奇幻</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>1961</td>\n",
       "      <td>114</td>\n",
       "      <td>9.3</td>\n",
       "      <td>243233</td>\n",
       "      <td>432337</td>\n",
       "      <td>91536</td>\n",
       "      <td>24455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>59</td>\n",
       "      <td>饮食男女</td>\n",
       "      <td>李安</td>\n",
       "      <td>李安 / 王蕙玲 / 詹姆斯·夏慕斯</td>\n",
       "      <td>郎雄 / 杨贵媚 / 吴倩莲</td>\n",
       "      <td>剧情/家庭</td>\n",
       "      <td>中国台湾 / 美国</td>\n",
       "      <td>汉语普通话 / 闽南语 / 湖南话</td>\n",
       "      <td>1994</td>\n",
       "      <td>124</td>\n",
       "      <td>9.1</td>\n",
       "      <td>373617</td>\n",
       "      <td>514844</td>\n",
       "      <td>202161</td>\n",
       "      <td>82989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>66</td>\n",
       "      <td>让子弹飞</td>\n",
       "      <td>姜文</td>\n",
       "      <td>朱苏进 / 述平 / 姜文 / 郭俊立 / 危笑 / 李不空 / 马识途</td>\n",
       "      <td>姜文 / 葛优 / 周润发</td>\n",
       "      <td>剧情/喜剧/动作/西部</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>汉语普通话 / 四川话 / 山西话</td>\n",
       "      <td>2010</td>\n",
       "      <td>132</td>\n",
       "      <td>8.8</td>\n",
       "      <td>1080619</td>\n",
       "      <td>1819080</td>\n",
       "      <td>120991</td>\n",
       "      <td>189474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>81</td>\n",
       "      <td>春光乍泄</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>张国荣 / 梁朝伟 / 张震</td>\n",
       "      <td>剧情/爱情/同性</td>\n",
       "      <td>中国香港 / 日本 / 韩国</td>\n",
       "      <td>粤语 / 汉语普通话 / 西班牙语</td>\n",
       "      <td>1997</td>\n",
       "      <td>96</td>\n",
       "      <td>8.9</td>\n",
       "      <td>419384</td>\n",
       "      <td>588842</td>\n",
       "      <td>218326</td>\n",
       "      <td>83686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>94</td>\n",
       "      <td>喜剧之王</td>\n",
       "      <td>周星驰</td>\n",
       "      <td>曾瑾昌 / 周星驰 / 李敏 / 郑文辉 / 冯勉恒 / 梁嘉杰</td>\n",
       "      <td>周星驰 / 张柏芝 / 莫文蔚</td>\n",
       "      <td>剧情/喜剧/爱情</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语</td>\n",
       "      <td>1999</td>\n",
       "      <td>85</td>\n",
       "      <td>8.7</td>\n",
       "      <td>613730</td>\n",
       "      <td>1071136</td>\n",
       "      <td>94263</td>\n",
       "      <td>79528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>100</td>\n",
       "      <td>阳光灿烂的日子</td>\n",
       "      <td>姜文</td>\n",
       "      <td>姜文 / 王朔</td>\n",
       "      <td>夏雨 / 宁静 / 陶虹</td>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>1995</td>\n",
       "      <td>134</td>\n",
       "      <td>8.8</td>\n",
       "      <td>426854</td>\n",
       "      <td>640542</td>\n",
       "      <td>176796</td>\n",
       "      <td>70875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>101</td>\n",
       "      <td>重庆森林</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>林青霞 / 金城武 / 梁朝伟</td>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语 / 汉语普通话 / 英语 / 印地语 / 日语</td>\n",
       "      <td>1994</td>\n",
       "      <td>102</td>\n",
       "      <td>8.7</td>\n",
       "      <td>535135</td>\n",
       "      <td>790205</td>\n",
       "      <td>196531</td>\n",
       "      <td>106779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>112</td>\n",
       "      <td>一一</td>\n",
       "      <td>杨德昌</td>\n",
       "      <td>杨德昌</td>\n",
       "      <td>吴念真 / 李凯莉 / 金燕玲</td>\n",
       "      <td>剧情/爱情/家庭</td>\n",
       "      <td>中国台湾 / 日本</td>\n",
       "      <td>汉语普通话 / 闽南语 / 英语 / 日语</td>\n",
       "      <td>2017</td>\n",
       "      <td>173</td>\n",
       "      <td>9.0</td>\n",
       "      <td>235598</td>\n",
       "      <td>317942</td>\n",
       "      <td>262772</td>\n",
       "      <td>62648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>117</td>\n",
       "      <td>射雕英雄传之东成西就</td>\n",
       "      <td>刘镇伟</td>\n",
       "      <td>刘镇伟</td>\n",
       "      <td>梁朝伟 / 林青霞 / 张国荣</td>\n",
       "      <td>喜剧/奇幻/武侠/古装</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语</td>\n",
       "      <td>1993</td>\n",
       "      <td>113</td>\n",
       "      <td>8.7</td>\n",
       "      <td>438014</td>\n",
       "      <td>698718</td>\n",
       "      <td>65343</td>\n",
       "      <td>65544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>120</td>\n",
       "      <td>倩女幽魂</td>\n",
       "      <td>程小东</td>\n",
       "      <td>阮继志</td>\n",
       "      <td>张国荣 / 王祖贤 / 午马</td>\n",
       "      <td>爱情/奇幻/武侠/古装</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语</td>\n",
       "      <td>1987</td>\n",
       "      <td>98</td>\n",
       "      <td>8.7</td>\n",
       "      <td>469113</td>\n",
       "      <td>921631</td>\n",
       "      <td>69723</td>\n",
       "      <td>58398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>121</td>\n",
       "      <td>唐伯虎点秋香</td>\n",
       "      <td>李力持</td>\n",
       "      <td>李力持 / 谷德昭 / 陈文强</td>\n",
       "      <td>周星驰 / 巩俐 / 陈百祥</td>\n",
       "      <td>喜剧/爱情/古装</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语</td>\n",
       "      <td>1993</td>\n",
       "      <td>102</td>\n",
       "      <td>8.6</td>\n",
       "      <td>660217</td>\n",
       "      <td>1233556</td>\n",
       "      <td>24760</td>\n",
       "      <td>55640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>122</td>\n",
       "      <td>甜蜜蜜</td>\n",
       "      <td>陈可辛</td>\n",
       "      <td>岸西</td>\n",
       "      <td>黎明 / 张曼玉 / 杨恭如</td>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语 / 汉语普通话 / 英语</td>\n",
       "      <td>1996</td>\n",
       "      <td>118</td>\n",
       "      <td>8.8</td>\n",
       "      <td>345575</td>\n",
       "      <td>495593</td>\n",
       "      <td>145576</td>\n",
       "      <td>69274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>142</td>\n",
       "      <td>喜宴</td>\n",
       "      <td>李安</td>\n",
       "      <td>李安 / 冯光远 / 詹姆斯·夏慕斯</td>\n",
       "      <td>赵文瑄 / 郎雄 / 归亚蕾</td>\n",
       "      <td>剧情/喜剧/爱情/同性/家庭</td>\n",
       "      <td>中国台湾 / 美国</td>\n",
       "      <td>汉语普通话 / 英语</td>\n",
       "      <td>1993</td>\n",
       "      <td>108</td>\n",
       "      <td>8.9</td>\n",
       "      <td>225475</td>\n",
       "      <td>296156</td>\n",
       "      <td>139123</td>\n",
       "      <td>46879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>144</td>\n",
       "      <td>岁月神偷</td>\n",
       "      <td>罗启锐</td>\n",
       "      <td>罗启锐 / 张婉婷</td>\n",
       "      <td>吴君如 / 任达华 / 钟绍图</td>\n",
       "      <td>剧情/家庭</td>\n",
       "      <td>中国香港 / 中国大陆</td>\n",
       "      <td>粤语 / 汉语普通话 / 英语 / 上海话 / 法语</td>\n",
       "      <td>2010</td>\n",
       "      <td>117</td>\n",
       "      <td>8.7</td>\n",
       "      <td>434379</td>\n",
       "      <td>640265</td>\n",
       "      <td>168445</td>\n",
       "      <td>95105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>146</td>\n",
       "      <td>英雄本色</td>\n",
       "      <td>吴宇森</td>\n",
       "      <td>陈庆嘉 / 吴宇森 / 梁淑华</td>\n",
       "      <td>周润发 / 狄龙 / 张国荣</td>\n",
       "      <td>剧情/动作/犯罪</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语 / 汉语普通话 / 英语</td>\n",
       "      <td>1986</td>\n",
       "      <td>95</td>\n",
       "      <td>8.7</td>\n",
       "      <td>327804</td>\n",
       "      <td>620116</td>\n",
       "      <td>91755</td>\n",
       "      <td>43187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>153</td>\n",
       "      <td>心迷宫</td>\n",
       "      <td>忻钰坤</td>\n",
       "      <td>忻钰坤 / 冯元良 / 鲁妮凡</td>\n",
       "      <td>霍卫民 / 王笑天 / 罗芸</td>\n",
       "      <td>剧情/悬疑/犯罪</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>2015</td>\n",
       "      <td>110</td>\n",
       "      <td>8.7</td>\n",
       "      <td>323517</td>\n",
       "      <td>435055</td>\n",
       "      <td>182155</td>\n",
       "      <td>79576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>154</td>\n",
       "      <td>哪吒闹海</td>\n",
       "      <td>严定宪</td>\n",
       "      <td>王树忱</td>\n",
       "      <td>梁正晖 / 邱岳峰 / 毕克</td>\n",
       "      <td>动画/奇幻/冒险</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>1979</td>\n",
       "      <td>65</td>\n",
       "      <td>9.0</td>\n",
       "      <td>159517</td>\n",
       "      <td>269068</td>\n",
       "      <td>50752</td>\n",
       "      <td>16813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>155</td>\n",
       "      <td>纵横四海</td>\n",
       "      <td>吴宇森</td>\n",
       "      <td>吴宇森 / 高志森 / 秦小珍</td>\n",
       "      <td>周润发 / 张国荣 / 钟楚红</td>\n",
       "      <td>剧情/喜剧/动作/犯罪</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语 / 汉语普通话 / 客家话 / 英语 / 法语</td>\n",
       "      <td>1991</td>\n",
       "      <td>108</td>\n",
       "      <td>8.8</td>\n",
       "      <td>266136</td>\n",
       "      <td>434602</td>\n",
       "      <td>83417</td>\n",
       "      <td>40912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>156</td>\n",
       "      <td>功夫</td>\n",
       "      <td>周星驰</td>\n",
       "      <td>曾瑾昌 / 陈文强 / 周星驰 / 霍昕</td>\n",
       "      <td>周星驰 / 元秋 / 元华</td>\n",
       "      <td>喜剧/动作/犯罪/奇幻</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>粤语 / 汉语普通话 / 手语</td>\n",
       "      <td>2004</td>\n",
       "      <td>100</td>\n",
       "      <td>8.5</td>\n",
       "      <td>597823</td>\n",
       "      <td>1053198</td>\n",
       "      <td>23033</td>\n",
       "      <td>59884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>158</td>\n",
       "      <td>东邪西毒</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫 / 金庸</td>\n",
       "      <td>张国荣 / 林青霞 / 梁朝伟</td>\n",
       "      <td>剧情/动作/爱情/武侠/古装</td>\n",
       "      <td>中国香港 / 中国台湾</td>\n",
       "      <td>粤语 / 汉语普通话</td>\n",
       "      <td>1994</td>\n",
       "      <td>100</td>\n",
       "      <td>8.6</td>\n",
       "      <td>409443</td>\n",
       "      <td>750473</td>\n",
       "      <td>144297</td>\n",
       "      <td>58865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>163</td>\n",
       "      <td>天书奇谭</td>\n",
       "      <td>王树忱</td>\n",
       "      <td>王树忱 / 包蕾</td>\n",
       "      <td>丁建华 / 毕克 / 苏秀</td>\n",
       "      <td>动画/奇幻</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>1983</td>\n",
       "      <td>89</td>\n",
       "      <td>9.2</td>\n",
       "      <td>125373</td>\n",
       "      <td>198811</td>\n",
       "      <td>35175</td>\n",
       "      <td>13806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>167</td>\n",
       "      <td>花样年华</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>梁朝伟 / 张曼玉 / 潘迪华</td>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语 / 上海话 / 法语</td>\n",
       "      <td>2000</td>\n",
       "      <td>98</td>\n",
       "      <td>8.6</td>\n",
       "      <td>380579</td>\n",
       "      <td>576588</td>\n",
       "      <td>133869</td>\n",
       "      <td>70478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>195</td>\n",
       "      <td>疯狂的石头</td>\n",
       "      <td>宁浩</td>\n",
       "      <td>张承 / 宁浩 / 岳小军</td>\n",
       "      <td>郭涛 / 刘桦 / 连晋</td>\n",
       "      <td>喜剧/犯罪</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>汉语普通话 / 重庆话</td>\n",
       "      <td>2006</td>\n",
       "      <td>106</td>\n",
       "      <td>8.4</td>\n",
       "      <td>533114</td>\n",
       "      <td>897255</td>\n",
       "      <td>71175</td>\n",
       "      <td>57532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>198</td>\n",
       "      <td>奇迹男孩</td>\n",
       "      <td>斯蒂芬·卓博斯基</td>\n",
       "      <td>斯蒂芬·卓博斯基 / 斯蒂夫·康拉德 / 杰克·索恩 / R·J·帕拉西奥</td>\n",
       "      <td>雅各布·特伦布莱 / 朱莉娅·罗伯茨 / 伊扎贝拉·维多维奇</td>\n",
       "      <td>剧情/家庭/儿童</td>\n",
       "      <td>美国 / 中国香港</td>\n",
       "      <td>美国 / 中国香港</td>\n",
       "      <td>2018</td>\n",
       "      <td>113</td>\n",
       "      <td>8.6</td>\n",
       "      <td>384100</td>\n",
       "      <td>574735</td>\n",
       "      <td>170609</td>\n",
       "      <td>100752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>204</td>\n",
       "      <td>可可西里</td>\n",
       "      <td>陆川</td>\n",
       "      <td>陆川</td>\n",
       "      <td>多布杰 / 张正阳 / 奇道</td>\n",
       "      <td>剧情/犯罪</td>\n",
       "      <td>中国大陆 / 中国香港</td>\n",
       "      <td>汉语普通话 / 藏语</td>\n",
       "      <td>2004</td>\n",
       "      <td>85</td>\n",
       "      <td>8.8</td>\n",
       "      <td>195742</td>\n",
       "      <td>400106</td>\n",
       "      <td>132493</td>\n",
       "      <td>29108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>207</td>\n",
       "      <td>牯岭街少年杀人事件</td>\n",
       "      <td>杨德昌</td>\n",
       "      <td>杨德昌 / 赖铭堂 / 杨顺清 / 鸿鸿</td>\n",
       "      <td>张震 / 杨静怡 / 张国柱</td>\n",
       "      <td>剧情/犯罪</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>汉语普通话 / 闽南语 / 上海话 / 粤语</td>\n",
       "      <td>1991</td>\n",
       "      <td>237</td>\n",
       "      <td>8.8</td>\n",
       "      <td>171250</td>\n",
       "      <td>238062</td>\n",
       "      <td>227403</td>\n",
       "      <td>38949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>208</td>\n",
       "      <td>阿飞正传</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>张国荣 / 张曼玉 / 刘嘉玲</td>\n",
       "      <td>剧情/爱情/犯罪</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语 / 汉语普通话 / 英语 / 菲律宾语 / 上海话</td>\n",
       "      <td>1990</td>\n",
       "      <td>94</td>\n",
       "      <td>8.5</td>\n",
       "      <td>334622</td>\n",
       "      <td>515041</td>\n",
       "      <td>140385</td>\n",
       "      <td>65113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>216</td>\n",
       "      <td>新龙门客栈</td>\n",
       "      <td>李惠民</td>\n",
       "      <td>徐克 / 张炭 / 吕晓禾 / 司徒慧焯 / 何冀平 / 苏叔阳</td>\n",
       "      <td>张曼玉 / 林青霞 / 梁家辉</td>\n",
       "      <td>动作/爱情/武侠/古装</td>\n",
       "      <td>中国香港 / 中国大陆</td>\n",
       "      <td>汉语普通话 / 粤语</td>\n",
       "      <td>1992</td>\n",
       "      <td>88</td>\n",
       "      <td>8.6</td>\n",
       "      <td>296646</td>\n",
       "      <td>479900</td>\n",
       "      <td>57875</td>\n",
       "      <td>34305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>218</td>\n",
       "      <td>青蛇</td>\n",
       "      <td>徐克</td>\n",
       "      <td>李碧华 / 徐克</td>\n",
       "      <td>张曼玉 / 王祖贤 / 赵文卓</td>\n",
       "      <td>剧情/爱情/奇幻/古装</td>\n",
       "      <td>中国香港</td>\n",
       "      <td>粤语</td>\n",
       "      <td>1993</td>\n",
       "      <td>99</td>\n",
       "      <td>8.5</td>\n",
       "      <td>342544</td>\n",
       "      <td>542002</td>\n",
       "      <td>70703</td>\n",
       "      <td>51822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>228</td>\n",
       "      <td>色，戒</td>\n",
       "      <td>李安</td>\n",
       "      <td>王蕙玲 / 詹姆斯·夏慕斯 / 张爱玲</td>\n",
       "      <td>梁朝伟 / 汤唯 / 陈冲</td>\n",
       "      <td>剧情/爱情/情色</td>\n",
       "      <td>中国台湾 / 中国大陆 / 美国 / 中国香港</td>\n",
       "      <td>汉语普通话 / 上海话 / 英语 / 粤语 / 日语 / 印地语</td>\n",
       "      <td>2007</td>\n",
       "      <td>158</td>\n",
       "      <td>8.4</td>\n",
       "      <td>440214</td>\n",
       "      <td>682822</td>\n",
       "      <td>146330</td>\n",
       "      <td>73486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>230</td>\n",
       "      <td>大佛普拉斯</td>\n",
       "      <td>黄信尧</td>\n",
       "      <td>黄信尧</td>\n",
       "      <td>庄益增 / 陈竹昇 / 戴立忍</td>\n",
       "      <td>剧情/喜剧/犯罪</td>\n",
       "      <td>中国台湾</td>\n",
       "      <td>闽南语 / 汉语普通话</td>\n",
       "      <td>2017</td>\n",
       "      <td>102</td>\n",
       "      <td>8.7</td>\n",
       "      <td>243382</td>\n",
       "      <td>298898</td>\n",
       "      <td>214754</td>\n",
       "      <td>64057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>237</td>\n",
       "      <td>驴得水</td>\n",
       "      <td>周申</td>\n",
       "      <td>周申 / 刘露</td>\n",
       "      <td>任素汐 / 大力 / 刘帅良</td>\n",
       "      <td>剧情/喜剧</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>2016</td>\n",
       "      <td>111</td>\n",
       "      <td>8.3</td>\n",
       "      <td>611231</td>\n",
       "      <td>951059</td>\n",
       "      <td>99651</td>\n",
       "      <td>155669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>247</td>\n",
       "      <td>二十二</td>\n",
       "      <td>郭柯</td>\n",
       "      <td>无</td>\n",
       "      <td>无</td>\n",
       "      <td>纪录片</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>2017</td>\n",
       "      <td>99</td>\n",
       "      <td>8.7</td>\n",
       "      <td>199246</td>\n",
       "      <td>368169</td>\n",
       "      <td>159145</td>\n",
       "      <td>52294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>249</td>\n",
       "      <td>四个春天</td>\n",
       "      <td>陆庆屹</td>\n",
       "      <td>无</td>\n",
       "      <td>陆运坤 / 李桂贤 / 陆庆伟 / 陆庆松 / 陆庆屹</td>\n",
       "      <td>纪录片 / 家庭</td>\n",
       "      <td>中国大陆</td>\n",
       "      <td>贵州独山话</td>\n",
       "      <td>2019</td>\n",
       "      <td>105</td>\n",
       "      <td>8.9</td>\n",
       "      <td>107290</td>\n",
       "      <td>147630</td>\n",
       "      <td>180634</td>\n",
       "      <td>42213</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0       Title   Director                           Screenwriter  \\\n",
       "1             1        霸王别姬        陈凯歌                               芦苇 / 李碧华   \n",
       "16           16   大话西游之大圣娶亲        刘镇伟                                    刘镇伟   \n",
       "20           20         无间道        刘伟强                              麦兆辉 / 庄文强   \n",
       "27           27          活着        张艺谋                                芦苇 / 余华   \n",
       "30           30    少年派的奇幻漂流         李安                          扬·马特尔 / 大卫·麦基   \n",
       "31           31        末代皇帝  贝纳尔多·贝托鲁奇                     贝纳尔多·贝托鲁奇 / 马克·派普罗   \n",
       "36           36        鬼子来了         姜文                    姜文 / 史建全 / 述平 / 尤凤伟   \n",
       "39           39   大话西游之月光宝盒        刘镇伟                              刘镇伟 / 吴承恩   \n",
       "53           53       我不是药神        文牧野                         韩家女 / 钟伟 / 文牧野   \n",
       "55           55        大闹天宫        万籁鸣                              李克弱 / 万籁鸣   \n",
       "59           59        饮食男女         李安                     李安 / 王蕙玲 / 詹姆斯·夏慕斯   \n",
       "66           66        让子弹飞         姜文   朱苏进 / 述平 / 姜文 / 郭俊立 / 危笑 / 李不空 / 马识途   \n",
       "81           81        春光乍泄        王家卫                                    王家卫   \n",
       "94           94        喜剧之王        周星驰       曾瑾昌 / 周星驰 / 李敏 / 郑文辉 / 冯勉恒 / 梁嘉杰   \n",
       "100         100     阳光灿烂的日子         姜文                                姜文 / 王朔   \n",
       "101         101        重庆森林        王家卫                                    王家卫   \n",
       "112         112          一一        杨德昌                                    杨德昌   \n",
       "117         117  射雕英雄传之东成西就        刘镇伟                                    刘镇伟   \n",
       "120         120        倩女幽魂        程小东                                    阮继志   \n",
       "121         121      唐伯虎点秋香        李力持                        李力持 / 谷德昭 / 陈文强   \n",
       "122         122         甜蜜蜜        陈可辛                                     岸西   \n",
       "142         142          喜宴         李安                     李安 / 冯光远 / 詹姆斯·夏慕斯   \n",
       "144         144        岁月神偷        罗启锐                              罗启锐 / 张婉婷   \n",
       "146         146        英雄本色        吴宇森                        陈庆嘉 / 吴宇森 / 梁淑华   \n",
       "153         153         心迷宫        忻钰坤                        忻钰坤 / 冯元良 / 鲁妮凡   \n",
       "154         154        哪吒闹海        严定宪                                    王树忱   \n",
       "155         155        纵横四海        吴宇森                        吴宇森 / 高志森 / 秦小珍   \n",
       "156         156          功夫        周星驰                   曾瑾昌 / 陈文强 / 周星驰 / 霍昕   \n",
       "158         158        东邪西毒        王家卫                               王家卫 / 金庸   \n",
       "163         163        天书奇谭        王树忱                               王树忱 / 包蕾   \n",
       "167         167        花样年华        王家卫                                    王家卫   \n",
       "195         195       疯狂的石头         宁浩                          张承 / 宁浩 / 岳小军   \n",
       "198         198        奇迹男孩   斯蒂芬·卓博斯基  斯蒂芬·卓博斯基 / 斯蒂夫·康拉德 / 杰克·索恩 / R·J·帕拉西奥   \n",
       "204         204        可可西里         陆川                                     陆川   \n",
       "207         207   牯岭街少年杀人事件        杨德昌                   杨德昌 / 赖铭堂 / 杨顺清 / 鸿鸿   \n",
       "208         208        阿飞正传        王家卫                                    王家卫   \n",
       "216         216       新龙门客栈        李惠民       徐克 / 张炭 / 吕晓禾 / 司徒慧焯 / 何冀平 / 苏叔阳   \n",
       "218         218          青蛇         徐克                               李碧华 / 徐克   \n",
       "228         228         色，戒         李安                    王蕙玲 / 詹姆斯·夏慕斯 / 张爱玲   \n",
       "230         230       大佛普拉斯        黄信尧                                    黄信尧   \n",
       "237         237         驴得水         周申                                周申 / 刘露   \n",
       "247         247         二十二         郭柯                                      无   \n",
       "249         249        四个春天        陆庆屹                                      无   \n",
       "\n",
       "                      Main_performer           Types  \\\n",
       "1                    张国荣 / 张丰毅 / 巩俐         剧情/爱情/同性   \n",
       "16                   周星驰 / 吴孟达 / 朱茵      喜剧/爱情/奇幻/古装   \n",
       "20                  刘德华 / 梁朝伟 / 黄秋生         剧情/悬疑/犯罪   \n",
       "27                     葛优 / 巩俐 / 姜武         剧情/家庭/历史   \n",
       "30           苏拉·沙玛 / 伊尔凡·可汗 / 拉菲·斯波         剧情/奇幻/冒险   \n",
       "31                    尊龙 / 陈冲 / 邬君梅         剧情/传记/历史   \n",
       "36                   姜文 / 香川照之 / 袁丁         剧情/历史/战争   \n",
       "39                  周星驰 / 吴孟达 / 罗家英      喜剧/爱情/奇幻/古装   \n",
       "53                   徐峥 / 王传君 / 周一围            剧情/喜剧   \n",
       "55                   邱岳峰 / 富润生 / 毕克            动画/奇幻   \n",
       "59                   郎雄 / 杨贵媚 / 吴倩莲            剧情/家庭   \n",
       "66                    姜文 / 葛优 / 周润发      剧情/喜剧/动作/西部   \n",
       "81                    张国荣 / 梁朝伟 / 张震        剧情/爱情/同性   \n",
       "94                  周星驰 / 张柏芝 / 莫文蔚         剧情/喜剧/爱情   \n",
       "100                    夏雨 / 宁静 / 陶虹            剧情/爱情   \n",
       "101                 林青霞 / 金城武 / 梁朝伟            剧情/爱情   \n",
       "112                 吴念真 / 李凯莉 / 金燕玲         剧情/爱情/家庭   \n",
       "117                 梁朝伟 / 林青霞 / 张国荣      喜剧/奇幻/武侠/古装   \n",
       "120                  张国荣 / 王祖贤 / 午马      爱情/奇幻/武侠/古装   \n",
       "121                  周星驰 / 巩俐 / 陈百祥         喜剧/爱情/古装   \n",
       "122                  黎明 / 张曼玉 / 杨恭如            剧情/爱情   \n",
       "142                  赵文瑄 / 郎雄 / 归亚蕾   剧情/喜剧/爱情/同性/家庭   \n",
       "144                 吴君如 / 任达华 / 钟绍图            剧情/家庭   \n",
       "146                  周润发 / 狄龙 / 张国荣         剧情/动作/犯罪   \n",
       "153                  霍卫民 / 王笑天 / 罗芸         剧情/悬疑/犯罪   \n",
       "154                  梁正晖 / 邱岳峰 / 毕克         动画/奇幻/冒险   \n",
       "155                 周润发 / 张国荣 / 钟楚红      剧情/喜剧/动作/犯罪   \n",
       "156                   周星驰 / 元秋 / 元华      喜剧/动作/犯罪/奇幻   \n",
       "158                 张国荣 / 林青霞 / 梁朝伟   剧情/动作/爱情/武侠/古装   \n",
       "163                   丁建华 / 毕克 / 苏秀            动画/奇幻   \n",
       "167                 梁朝伟 / 张曼玉 / 潘迪华            剧情/爱情   \n",
       "195                    郭涛 / 刘桦 / 连晋            喜剧/犯罪   \n",
       "198  雅各布·特伦布莱 / 朱莉娅·罗伯茨 / 伊扎贝拉·维多维奇         剧情/家庭/儿童   \n",
       "204                  多布杰 / 张正阳 / 奇道            剧情/犯罪   \n",
       "207                  张震 / 杨静怡 / 张国柱            剧情/犯罪   \n",
       "208                 张国荣 / 张曼玉 / 刘嘉玲         剧情/爱情/犯罪   \n",
       "216                 张曼玉 / 林青霞 / 梁家辉      动作/爱情/武侠/古装   \n",
       "218                 张曼玉 / 王祖贤 / 赵文卓      剧情/爱情/奇幻/古装   \n",
       "228                   梁朝伟 / 汤唯 / 陈冲         剧情/爱情/情色   \n",
       "230                 庄益增 / 陈竹昇 / 戴立忍         剧情/喜剧/犯罪   \n",
       "237                  任素汐 / 大力 / 刘帅良            剧情/喜剧   \n",
       "247                                无             纪录片   \n",
       "249      陆运坤 / 李桂贤 / 陆庆伟 / 陆庆松 / 陆庆屹        纪录片 / 家庭   \n",
       "\n",
       "                       Region                           Language  ShowTime  \\\n",
       "1                 中国大陆 / 中国香港                              汉语普通话      1993   \n",
       "16                中国香港 / 中国大陆                         粤语 / 汉语普通话      1995   \n",
       "20                       中国香港                                 粤语      2002   \n",
       "27                中国大陆 / 中国香港                              汉语普通话      1994   \n",
       "30       美国 / 中国台湾 / 英国 / 加拿大               美国 / 中国台湾 / 英国 / 加拿大      2012   \n",
       "31       英国 / 意大利 / 中国大陆 / 法国                    英语 / 汉语普通话 / 日语      1987   \n",
       "36                       中国大陆                   汉语普通话 / 日语 / 唐山话      2000   \n",
       "39                中国香港 / 中国大陆                         粤语 / 汉语普通话      1995   \n",
       "53                       中国大陆             汉语普通话 / 英语 / 上海话 / 印地语      2018   \n",
       "55                       中国大陆                              汉语普通话      1961   \n",
       "59                  中国台湾 / 美国                  汉语普通话 / 闽南语 / 湖南话      1994   \n",
       "66                中国大陆 / 中国香港                  汉语普通话 / 四川话 / 山西话      2010   \n",
       "81             中国香港 / 日本 / 韩国                  粤语 / 汉语普通话 / 西班牙语      1997   \n",
       "94                       中国香港                                 粤语      1999   \n",
       "100               中国大陆 / 中国香港                              汉语普通话      1995   \n",
       "101                      中国香港         粤语 / 汉语普通话 / 英语 / 印地语 / 日语      1994   \n",
       "112                 中国台湾 / 日本              汉语普通话 / 闽南语 / 英语 / 日语      2017   \n",
       "117                      中国香港                                 粤语      1993   \n",
       "120                      中国香港                                 粤语      1987   \n",
       "121                      中国香港                                 粤语      1993   \n",
       "122                      中国香港                    粤语 / 汉语普通话 / 英语      1996   \n",
       "142                 中国台湾 / 美国                         汉语普通话 / 英语      1993   \n",
       "144               中国香港 / 中国大陆         粤语 / 汉语普通话 / 英语 / 上海话 / 法语      2010   \n",
       "146                      中国香港                    粤语 / 汉语普通话 / 英语      1986   \n",
       "153                      中国大陆                              汉语普通话      2015   \n",
       "154                      中国大陆                              汉语普通话      1979   \n",
       "155                      中国香港         粤语 / 汉语普通话 / 客家话 / 英语 / 法语      1991   \n",
       "156               中国大陆 / 中国香港                    粤语 / 汉语普通话 / 手语      2004   \n",
       "158               中国香港 / 中国台湾                         粤语 / 汉语普通话      1994   \n",
       "163                      中国大陆                              汉语普通话      1983   \n",
       "167                      中国香港                      粤语 / 上海话 / 法语      2000   \n",
       "195               中国大陆 / 中国香港                        汉语普通话 / 重庆话      2006   \n",
       "198                 美国 / 中国香港                          美国 / 中国香港      2018   \n",
       "204               中国大陆 / 中国香港                         汉语普通话 / 藏语      2004   \n",
       "207                      中国台湾             汉语普通话 / 闽南语 / 上海话 / 粤语      1991   \n",
       "208                      中国香港       粤语 / 汉语普通话 / 英语 / 菲律宾语 / 上海话      1990   \n",
       "216               中国香港 / 中国大陆                         汉语普通话 / 粤语      1992   \n",
       "218                      中国香港                                 粤语      1993   \n",
       "228   中国台湾 / 中国大陆 / 美国 / 中国香港   汉语普通话 / 上海话 / 英语 / 粤语 / 日语 / 印地语      2007   \n",
       "230                      中国台湾                        闽南语 / 汉语普通话      2017   \n",
       "237                      中国大陆                              汉语普通话      2016   \n",
       "247                      中国大陆                              汉语普通话      2017   \n",
       "249                      中国大陆                              贵州独山话      2019   \n",
       "\n",
       "     Film_length  Score  Rating_people  Watching_people  Wtsee_people  \\\n",
       "1            171    9.6        1373527          2075888        275105   \n",
       "16            95    9.2         992143          1621715        126432   \n",
       "20           101    9.2         811448          1341575        158992   \n",
       "27           132    9.2         526734           779096        272885   \n",
       "30           127    9.1         971460          1495187        194292   \n",
       "31           163    9.2         459153           698624        256309   \n",
       "36           139    9.2         416646           631875        208134   \n",
       "39            87    9.0         799583          1426088         67887   \n",
       "53           117    9.0        1391409          4045012        852656   \n",
       "55           114    9.3         243233           432337         91536   \n",
       "59           124    9.1         373617           514844        202161   \n",
       "66           132    8.8        1080619          1819080        120991   \n",
       "81            96    8.9         419384           588842        218326   \n",
       "94            85    8.7         613730          1071136         94263   \n",
       "100          134    8.8         426854           640542        176796   \n",
       "101          102    8.7         535135           790205        196531   \n",
       "112          173    9.0         235598           317942        262772   \n",
       "117          113    8.7         438014           698718         65343   \n",
       "120           98    8.7         469113           921631         69723   \n",
       "121          102    8.6         660217          1233556         24760   \n",
       "122          118    8.8         345575           495593        145576   \n",
       "142          108    8.9         225475           296156        139123   \n",
       "144          117    8.7         434379           640265        168445   \n",
       "146           95    8.7         327804           620116         91755   \n",
       "153          110    8.7         323517           435055        182155   \n",
       "154           65    9.0         159517           269068         50752   \n",
       "155          108    8.8         266136           434602         83417   \n",
       "156          100    8.5         597823          1053198         23033   \n",
       "158          100    8.6         409443           750473        144297   \n",
       "163           89    9.2         125373           198811         35175   \n",
       "167           98    8.6         380579           576588        133869   \n",
       "195          106    8.4         533114           897255         71175   \n",
       "198          113    8.6         384100           574735        170609   \n",
       "204           85    8.8         195742           400106        132493   \n",
       "207          237    8.8         171250           238062        227403   \n",
       "208           94    8.5         334622           515041        140385   \n",
       "216           88    8.6         296646           479900         57875   \n",
       "218           99    8.5         342544           542002         70703   \n",
       "228          158    8.4         440214           682822        146330   \n",
       "230          102    8.7         243382           298898        214754   \n",
       "237          111    8.3         611231           951059         99651   \n",
       "247           99    8.7         199246           368169        159145   \n",
       "249          105    8.9         107290           147630        180634   \n",
       "\n",
       "     Comments_people  \n",
       "1             272480  \n",
       "16            150276  \n",
       "20            109866  \n",
       "27            101208  \n",
       "30            216602  \n",
       "31             89290  \n",
       "36             71459  \n",
       "39             71830  \n",
       "53            387322  \n",
       "55             24455  \n",
       "59             82989  \n",
       "66            189474  \n",
       "81             83686  \n",
       "94             79528  \n",
       "100            70875  \n",
       "101           106779  \n",
       "112            62648  \n",
       "117            65544  \n",
       "120            58398  \n",
       "121            55640  \n",
       "122            69274  \n",
       "142            46879  \n",
       "144            95105  \n",
       "146            43187  \n",
       "153            79576  \n",
       "154            16813  \n",
       "155            40912  \n",
       "156            59884  \n",
       "158            58865  \n",
       "163            13806  \n",
       "167            70478  \n",
       "195            57532  \n",
       "198           100752  \n",
       "204            29108  \n",
       "207            38949  \n",
       "208            65113  \n",
       "216            34305  \n",
       "218            51822  \n",
       "228            73486  \n",
       "230            64057  \n",
       "237           155669  \n",
       "247            52294  \n",
       "249            42213  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "豆瓣电影_中国= Movie_info[ Movie_info.Region.str.contains(\"中国\")]  \n",
    "                       \n",
    "豆瓣电影_中国"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        vertical-align: top;\n",
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       "        text-align: left;\n",
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">Score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>min</th>\n",
       "      <th>mean</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>一一</th>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>东邪西毒</th>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>二十二</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>倩女幽魂</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>功夫</th>\n",
       "      <td>8.5</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>可可西里</th>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>哪吒闹海</th>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>唐伯虎点秋香</th>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>喜剧之王</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>喜宴</th>\n",
       "      <td>8.9</td>\n",
       "      <td>8.9</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>四个春天</th>\n",
       "      <td>8.9</td>\n",
       "      <td>8.9</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大佛普拉斯</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大话西游之大圣娶亲</th>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大话西游之月光宝盒</th>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大闹天宫</th>\n",
       "      <td>9.3</td>\n",
       "      <td>9.3</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>天书奇谭</th>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>奇迹男孩</th>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>射雕英雄传之东成西就</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>少年派的奇幻漂流</th>\n",
       "      <td>9.1</td>\n",
       "      <td>9.1</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>岁月神偷</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>心迷宫</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>我不是药神</th>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新龙门客栈</th>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>无间道</th>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>春光乍泄</th>\n",
       "      <td>8.9</td>\n",
       "      <td>8.9</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>末代皇帝</th>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>活着</th>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>牯岭街少年杀人事件</th>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>甜蜜蜜</th>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>疯狂的石头</th>\n",
       "      <td>8.4</td>\n",
       "      <td>8.4</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>纵横四海</th>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>色，戒</th>\n",
       "      <td>8.4</td>\n",
       "      <td>8.4</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>花样年华</th>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>英雄本色</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>让子弹飞</th>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>重庆森林</th>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阳光灿烂的日子</th>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阿飞正传</th>\n",
       "      <td>8.5</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>霸王别姬</th>\n",
       "      <td>9.6</td>\n",
       "      <td>9.6</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>青蛇</th>\n",
       "      <td>8.5</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>饮食男女</th>\n",
       "      <td>9.1</td>\n",
       "      <td>9.1</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>驴得水</th>\n",
       "      <td>8.3</td>\n",
       "      <td>8.3</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>鬼子来了</th>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Score          \n",
       "             min mean  max\n",
       "Title                     \n",
       "一一           9.0  9.0  9.0\n",
       "东邪西毒         8.6  8.6  8.6\n",
       "二十二          8.7  8.7  8.7\n",
       "倩女幽魂         8.7  8.7  8.7\n",
       "功夫           8.5  8.5  8.5\n",
       "可可西里         8.8  8.8  8.8\n",
       "哪吒闹海         9.0  9.0  9.0\n",
       "唐伯虎点秋香       8.6  8.6  8.6\n",
       "喜剧之王         8.7  8.7  8.7\n",
       "喜宴           8.9  8.9  8.9\n",
       "四个春天         8.9  8.9  8.9\n",
       "大佛普拉斯        8.7  8.7  8.7\n",
       "大话西游之大圣娶亲    9.2  9.2  9.2\n",
       "大话西游之月光宝盒    9.0  9.0  9.0\n",
       "大闹天宫         9.3  9.3  9.3\n",
       "天书奇谭         9.2  9.2  9.2\n",
       "奇迹男孩         8.6  8.6  8.6\n",
       "射雕英雄传之东成西就   8.7  8.7  8.7\n",
       "少年派的奇幻漂流     9.1  9.1  9.1\n",
       "岁月神偷         8.7  8.7  8.7\n",
       "心迷宫          8.7  8.7  8.7\n",
       "我不是药神        9.0  9.0  9.0\n",
       "新龙门客栈        8.6  8.6  8.6\n",
       "无间道          9.2  9.2  9.2\n",
       "春光乍泄         8.9  8.9  8.9\n",
       "末代皇帝         9.2  9.2  9.2\n",
       "活着           9.2  9.2  9.2\n",
       "牯岭街少年杀人事件    8.8  8.8  8.8\n",
       "甜蜜蜜          8.8  8.8  8.8\n",
       "疯狂的石头        8.4  8.4  8.4\n",
       "纵横四海         8.8  8.8  8.8\n",
       "色，戒          8.4  8.4  8.4\n",
       "花样年华         8.6  8.6  8.6\n",
       "英雄本色         8.7  8.7  8.7\n",
       "让子弹飞         8.8  8.8  8.8\n",
       "重庆森林         8.7  8.7  8.7\n",
       "阳光灿烂的日子      8.8  8.8  8.8\n",
       "阿飞正传         8.5  8.5  8.5\n",
       "霸王别姬         9.6  9.6  9.6\n",
       "青蛇           8.5  8.5  8.5\n",
       "饮食男女         9.1  9.1  9.1\n",
       "驴得水          8.3  8.3  8.3\n",
       "鬼子来了         9.2  9.2  9.2"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "豆瓣电影_中国.groupby(['Title']).agg({\"Score\":[\"min\",\"mean\",\"max\"]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>剧情/喜剧</td>\n",
       "      <td>文牧野</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>动画/奇幻</td>\n",
       "      <td>万籁鸣</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>剧情/家庭</td>\n",
       "      <td>李安</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>剧情/喜剧/动作/西部</td>\n",
       "      <td>姜文</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>剧情/爱情/同性</td>\n",
       "      <td>王家卫</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>剧情/喜剧/爱情</td>\n",
       "      <td>周星驰</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>姜文</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>王家卫</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>剧情/爱情/家庭</td>\n",
       "      <td>杨德昌</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>喜剧/奇幻/武侠/古装</td>\n",
       "      <td>刘镇伟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>爱情/奇幻/武侠/古装</td>\n",
       "      <td>程小东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>喜剧/爱情/古装</td>\n",
       "      <td>李力持</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>陈可辛</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>剧情/喜剧/爱情/同性/家庭</td>\n",
       "      <td>李安</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>剧情/家庭</td>\n",
       "      <td>罗启锐</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>剧情/动作/犯罪</td>\n",
       "      <td>吴宇森</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>剧情/悬疑/犯罪</td>\n",
       "      <td>忻钰坤</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>动画/奇幻/冒险</td>\n",
       "      <td>严定宪</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>剧情/喜剧/动作/犯罪</td>\n",
       "      <td>吴宇森</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>喜剧/动作/犯罪/奇幻</td>\n",
       "      <td>周星驰</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>剧情/动作/爱情/武侠/古装</td>\n",
       "      <td>王家卫</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>动画/奇幻</td>\n",
       "      <td>王树忱</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>剧情/爱情</td>\n",
       "      <td>王家卫</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>喜剧/犯罪</td>\n",
       "      <td>宁浩</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>剧情/家庭/儿童</td>\n",
       "      <td>斯蒂芬·卓博斯基</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>剧情/犯罪</td>\n",
       "      <td>陆川</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>剧情/犯罪</td>\n",
       "      <td>杨德昌</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>剧情/爱情/犯罪</td>\n",
       "      <td>王家卫</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>动作/爱情/武侠/古装</td>\n",
       "      <td>李惠民</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>剧情/爱情/奇幻/古装</td>\n",
       "      <td>徐克</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>剧情/爱情/情色</td>\n",
       "      <td>李安</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>剧情/喜剧/犯罪</td>\n",
       "      <td>黄信尧</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>剧情/喜剧</td>\n",
       "      <td>周申</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>纪录片</td>\n",
       "      <td>郭柯</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>纪录片 / 家庭</td>\n",
       "      <td>陆庆屹</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Types   Director\n",
       "0         剧情/爱情/同性        陈凯歌\n",
       "1      喜剧/爱情/奇幻/古装        刘镇伟\n",
       "2         剧情/悬疑/犯罪        刘伟强\n",
       "3         剧情/家庭/历史        张艺谋\n",
       "4         剧情/奇幻/冒险         李安\n",
       "5         剧情/传记/历史  贝纳尔多·贝托鲁奇\n",
       "6         剧情/历史/战争         姜文\n",
       "7      喜剧/爱情/奇幻/古装        刘镇伟\n",
       "8            剧情/喜剧        文牧野\n",
       "9            动画/奇幻        万籁鸣\n",
       "10           剧情/家庭         李安\n",
       "11     剧情/喜剧/动作/西部         姜文\n",
       "12        剧情/爱情/同性        王家卫\n",
       "13        剧情/喜剧/爱情        周星驰\n",
       "14           剧情/爱情         姜文\n",
       "15           剧情/爱情        王家卫\n",
       "16        剧情/爱情/家庭        杨德昌\n",
       "17     喜剧/奇幻/武侠/古装        刘镇伟\n",
       "18     爱情/奇幻/武侠/古装        程小东\n",
       "19        喜剧/爱情/古装        李力持\n",
       "20           剧情/爱情        陈可辛\n",
       "21  剧情/喜剧/爱情/同性/家庭         李安\n",
       "22           剧情/家庭        罗启锐\n",
       "23        剧情/动作/犯罪        吴宇森\n",
       "24        剧情/悬疑/犯罪        忻钰坤\n",
       "25        动画/奇幻/冒险        严定宪\n",
       "26     剧情/喜剧/动作/犯罪        吴宇森\n",
       "27     喜剧/动作/犯罪/奇幻        周星驰\n",
       "28  剧情/动作/爱情/武侠/古装        王家卫\n",
       "29           动画/奇幻        王树忱\n",
       "30           剧情/爱情        王家卫\n",
       "31           喜剧/犯罪         宁浩\n",
       "32        剧情/家庭/儿童   斯蒂芬·卓博斯基\n",
       "33           剧情/犯罪         陆川\n",
       "34           剧情/犯罪        杨德昌\n",
       "35        剧情/爱情/犯罪        王家卫\n",
       "36     动作/爱情/武侠/古装        李惠民\n",
       "37     剧情/爱情/奇幻/古装         徐克\n",
       "38        剧情/爱情/情色         李安\n",
       "39        剧情/喜剧/犯罪        黄信尧\n",
       "40           剧情/喜剧         周申\n",
       "41             纪录片         郭柯\n",
       "42        纪录片 / 家庭        陆庆屹"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "豆瓣_导演 = 豆瓣电影_中国.set_index(\"Types\")[['Director']].copy()\n",
    "豆瓣_导演.Director.apply(pd.Series)\\\n",
    "            .reset_index()\\\n",
    "            .melt(id_vars='Types', value_name='Director')\\\n",
    "            .drop(\"variable\", axis = 1)\\\n",
    "            .dropna()\\\n",
    "            .reset_index(drop=True)"
   ]
  }
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